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Cengiz, Enes, Muhammed Mustafa Kelek, Yüksel Oğuz, and Cemal Yılmaz. "Classification of breast cancer with deep learning from noisy images using wavelet transform." Biomedical Engineering / Biomedizinische Technik 67, no. 2 (2022): 143–50. http://dx.doi.org/10.1515/bmt-2021-0163.
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Abstract In this study, breast cancer classification as benign or malignant was made using images obtained by histopathological procedures, one of the medical imaging techniques. First of all, different noise types and several intensities were added to the images in the used data set. Then, the noise in images was removed by applying the Wavelet Transform (WT) process to noisy images. The performance rates in the denoising process were found out by evaluating Peak Signal to Noise Rate (PSNR) values of the images. The Gaussian noise type gave better results than other noise types considering PSNR values. The best PSNR values were carried out with the Gaussian noise type. After that, the denoised images were classified by Convolution Neural Network (CNN), one of the deep learning techniques. In this classification process, the proposed CNN model and the VggNet-16 model were used. According to the classification result, better results were obtained with the proposed CNN model than VggNet-16. The best performance (86.9%) was obtained from the data set created Gaussian noise with 0.3 noise intensity.
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Yunus, Mahmuddin, and Agus Harjoko. "Penyembunyian Data pada File Video Menggunakan Metode LSB dan DCT." IJCCS (Indonesian Journal of Computing and Cybernetics Systems) 8, no. 1 (2014): 81. http://dx.doi.org/10.22146/ijccs.3498.
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AbstrakPenyembunyian data pada file video dikenal dengan istilah steganografi video. Metode steganografi yang dikenal diantaranya metode Least Significant Bit (LSB) dan Discrete Cosine Transform (DCT). Dalam penelitian ini dilakukan penyembunyian data pada file video dengan menggunakan metode LSB, metode DCT, dan gabungan metode LSB-DCT. Sedangkan kualitas file video yang dihasilkan setelah penyisipan dihitung dengan menggunakan Mean Square Error (MSE) dan Peak Signal to Noise Ratio (PSNR).Uji eksperimen dilakukan berdasarkan ukuran file video, ukuran file berkas rahasia yang disisipkan, dan resolusi video.Hasil pengujian menunjukkan tingkat keberhasilan steganografi video dengan menggunakan metode LSB adalah 38%, metode DCT adalah 90%, dan gabungan metode LSB-DCT adalah 64%. Sedangkan hasil perhitungan MSE, nilai MSE metode DCT paling rendah dibandingkan metode LSB dan gabungan metode LSB-DCT. Sedangkan metode LSB-DCT mempunyai nilai yang lebih kecil dibandingkan metode LSB. Pada pengujian PSNR diperoleh databahwa nilai PSNR metode DCTlebih tinggi dibandingkan metode LSB dan gabungan metode LSB-DCT. Sedangkan nilai PSNR metode gabungan LSB-DCT lebih tinggi dibandingkan metode LSB. Kata Kunci—Steganografi, Video, Least Significant Bit (LSB), Discrete Cosine Transform (DCT), Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR) AbstractHiding data in video files is known as video steganography. Some of the well known steganography methods areLeast Significant Bit (LSB) and Discrete Cosine Transform (DCT) method. In this research, data will be hidden on the video file with LSB method, DCT method, and the combined method of LSB-DCT. While the quality result of video file after insertion is calculated using the Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR). The experiments were conducted based on the size of the video file, the file size of the inserted secret files, and video resolution.The test results showed that the success rate of the video steganography using LSB method was 38%, DCT method was 90%, and the combined method of LSB-DCT was 64%. While the calculation of MSE, the MSE method DCT lower than the combined method of LSB and LSB-DCT method. While LSB-DCT method has asmaller value than the LSB method. The PNSR experiment showed that the DCT method PSNR value is higher than the combined method of LSB and LSB-DCT method. While PSNR combined method LSB-DCT higher compared LSB method. Keywords—Steganography, Video, Least Significant Bit (LSB), Discrete Cosine Transform (DCT), Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR)
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Tyukhtyaev, Dmitry. "Researching Video Conference Services on IEEE 802.11x Wireless Networks." NBI Technologies, no. 4 (December 2021): 13–18. http://dx.doi.org/10.15688/nbit.jvolsu.2021.4.2.
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The purpose of the study was to determine the dependence of the quality of video conferencing services on the characteristics of wireless communication channels and the number of users in a given network. The characteristics of the signal strength in a wireless network, measured in decibels (dB) were described in this article. The article discusses subjective and objective methods for assessing video. The PSNR and VQM metrics and the MSU Video Quality Measurement Tool software, created by the computer graphics laboratory of the Moscow State University, were used as an objective method for assessing video. For the subjective method, the DSCQS method was used. The PSNR (peak signal to noise ratio) metric is one of the most commonly used metrics. PSNR measures the peak signal-to-noise ratio between the original signal and the signal at the output of the system. PSNR does not measure all video-specific parameters, as the fidelity of the image is constantly changing depending on the visual complexity of the image, the available bit rate and even the compression method. The Video Quality Measurement (VQM) metric is described in Recommendation ITU-R BT.1683. The test results show that VQM has a high correlation with subjective methods for assessing video quality and claims to become the standard in the field of objective quality assessment.
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Youssif, Mohamed Ibrahim, Amr ElSayed Emam, and Mohamed Abd ElGhany. "Image multiplexing using residue number system coding over MIMO-OFDM communication system." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 6 (2019): 4815. http://dx.doi.org/10.11591/ijece.v9i6.pp4815-4825.
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<p>Image transmission over Orthogonal Frequency-Division Multiplexing (OFDM) communication system is prone to distortion and noise due to the encountered High-Peak-to-Average-Power-Ratio (PAPR) generated from the OFDM block. This paper studies the utilization of Residue Number System (RNS) as a coding scheme for digital image transmission over Multiple-Input-Multiple-Output (MIMO) – OFDM transceiver communication system. The use of the independent parallel feature of RNS, as well as the reduced signal amplitude to convert the input signal to parallel smaller residue signals, enable to reduce the signal PAPR, decreasing the signal distortion and the Bit Error Rate (BER). Consequently, improving the received Signal-to-Noise Ratio (SNR) and enhancing the received image quality. The performance analyzed though BER, and PAPR. Moreover, image quality measurement is achieved through evaluating the Mean Squared Error (MSE), Peak Signal to Noise Ratio (PSNR), and the correlation values between the initial and retrieved images. Simulation results had shown the performance of transmission/reception model with and without RNS coding implementation.</p><p> </p>
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M., I. Youssef, E. Emam A., and Abd Elghany M. "Image multiplexing using residue number system coding over MIMO-OFDM communication system." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 6 (2019): 4815–25. https://doi.org/10.11591/ijece.v9i6.pp4815-4825.
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Image transmission over Orthogonal Frequency-Division Multiplexing (OFDM) communication system is prone to distortion and noise due to the encountered High-Peak-to-Average-Power-Ratio (PAPR) generated from the OFDM block. This paper studies the utilization of Residue Number System (RNS) as a coding scheme for digital image transmission over Multiple Input Multiple Output (MIMO) – OFDM transceiver communication system. The use of the independent parallel feature of RNS, as well as the reduced signal amplitude to convert the input signal to parallel smaller residue signals, enable to reduce the signal PAPR, decreasing the signal distortion and the Bit Error Rate (BER). Consequently, improving the received Signal-to-Noise Ratio (SNR) and enhancing the received image quality. The performance analyzed though BER, and PAPR. Moreover, image quality measurement is achieved through evaluating the Mean Squared Error (MSE), Peak Signal to Noise Ratio (PSNR), and the correlation values between the initial and retrieved images. Simulation results had shown the performance of transmission/reception model with and without RNS coding implementation.
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V, Malathi, and Gopinath MP. "Noise Deduction in Novel Paddy Data Repository using Filtering Techniques." Scalable Computing: Practice and Experience 21, no. 4 (2020): 601–10. http://dx.doi.org/10.12694/scpe.v21i4.1718.
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Classification of paddy crop diseases in prior knowledge is the current challenging task to evolve the economicgrowth of the country. In image processing techniques, the initial process is to eliminate the noise present in the dataset. Removing the noise leads to improvements in the quality of the image. Noise can be removed by applying filtering techniques. In this paper, a novel data repository created from different paddy areas in Vellore, which includes the following diseases, namely Bacteria Leaf Blight, Blast, Leaf Spot, Leaf Holder, Hispa and Healthy leaves. In the initial process, three kinds of noises, namely Salt and Pepper noise, Speckle noise, and Poisson noises, were removed using noise filtering techniques, namely Median and Wiener filter. Theinterpretation made over the median and Wiener filtering techniques concerning noises, the performance of the methods measured using metrics namely PSNR (peak to signal to noise ration), MSE (mean square error), Maxerr (Maximum squared error), L2rat (ratio of squared error). It is observed that the PSNR value of the hybrid approach is 18.42dB, which produces less error rate as compared with the traditional approach. Results suggest that the methods used in this paper are suitable for processing noise.
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Xu, Wanting, Hui Chen, Yuan Yuan, Sheng Luo, Huaibin Zheng, and Xiangan Yan. "High-fidelity sub-Nyquist ghost imaging with tri-directional probing." Journal of Applied Physics 131, no. 10 (2022): 103101. http://dx.doi.org/10.1063/5.0082828.
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Ghost imaging is an unconventional imaging method, which has invoked many applications in various fields. However, it is still a major challenge to achieve high-fidelity high-resolution images at a sub-Nyquist sampling rate. Here, we present a ghost imaging method that illuminates an object with three directional Tetris-like patterns, which can greatly trade off the contradiction between the high resolution and high detection signal-to-noise ratio. As the projected patterns gradually shrink during the detection, the image is also gradually recovered from low to high resolution. In addition, this method can recover complex chromatic objects without any compromising image quality by adaptively abandoning unnecessary patterns at sampling rates well below the Nyquist limit. Meanwhile, the dynamic probing scheme has an excellent noise-removal capability. The simulation and experiment demonstrate that the sampling rate to recover a high-fidelity image is only [Formula: see text] for a scene of a [Formula: see text] duty cycle. For a very noisy scene whose peak signal–noise rate (PSNR) is 10.18 dB [the structural similarity index (SSIM) is 0.068], this scheme increases the PSNR to 18.63 dB [structural similarity index (SSIM) to 0.73]. Therefore, the proposed method may be useful for ghost imaging in the low sampling rate regime or complex chromatic objects reconstruction.
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Qaswaa K. Abood. "Wavelet -Based Modified Intermediate Significant Bit Insertion for Text Steganography." Journal of the College of Basic Education 17, no. 70 (2022): 165–76. http://dx.doi.org/10.35950/cbej.vi.8486.
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In this paper, we propose and investigate the use of a modifiedversion of Intermediate Significant Bit (ISB) insertion algorithm, so-called here as MISB algorithm for secret text steganography. The secret text is passed through a sequence of ciphering techniques. A Modified Intermediate Significant Bit MISB insertion algorithm is proposed for hiding the bit sequences of the cipher text into the time-frequency domain using wavelet transform of the image pixels, in order to improve the robustness of the Steganography system. Results demonstrate the effectiveness of wavelet Modified Intermediate Significant Bit WMISB while evaluating its performance using Peak Signal to Noise Ratio PSNR measure. Moreover, additional experiments are evaluated for noising, and image compression for cover images to compare their Peak Signal to Noise Ratio PSNR. The drawn results confirm the effectiveness of the proposed Wavelet-based Modified Intermediate Significant Bit Insertion WMISB, Also, Bit Error Rate BER, is a key parameter that is used in assessing systems that transmit digital data from one location to another.
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Rahul, Nagraj, and Goud Myadaboyina Srinidhi. "Digital Signal Processing Algorithms for Noise Reduction in Wireless Image Transmission Systems." Sarcouncil Journal of Engineering and Computer Sciences 4, no. 3 (2025): 9–16. https://doi.org/10.5281/zenodo.15047488.
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Wireless Image Transmission Systems (WITS) are highly susceptible to noise distortions, leading to degraded image quality and increased transmission errors. This study evaluates the effectiveness of Digital Signal Processing (DSP) algorithms, Kalman filtering, wavelet-based denoising, Wiener filtering, and median filtering for noise reduction in WITS under varying Signal-to-Noise Ratio (SNR) levels (5 dB to 20 dB). Performance is assessed using Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), and Bit Error Rate (BER). The results indicate that Kalman filtering achieves the highest PSNR (33.2 dB) and SSIM (0.96), along with the lowest BER (0.005) at SNR = 20 dB, making it the most effective method for noise suppression. Wavelet-based denoising emerges as a computationally efficient alternative, offering a balance between image quality and processing speed. Statistical analyses, including ANOVA and paired t-tests, confirm significant differences (p < 0.001) in performance among the algorithms. The findings suggest that while Kalman filtering provides superior noise reduction, wavelet-based denoising is more suitable for real-time applications. Future research should explore hybrid DSP techniques and deep learning-based models for enhanced noise suppression in wireless imaging
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Lima, Regiano Karunia. "ANALISIS PERBANDINGAN REDUKSI NOISE MENGGUNAKAN METODE MEAN, MEDIAN DAN CONTRA-HARMONIC MEAN FILTERING PADA CITRA GRAYSCALE POLA TENUNAN DAERAH PROVINSI NUSA TENGGARA TIMUR." Jurnal Elektro dan Telekomunikasi Terapan 11, no. 1 (2024): 9–15. https://doi.org/10.25124/jett.v11i1.6827.
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Abstrak Baik atau tidaknya kualitas dari suatu citra digital dapat dipengaruhi oleh beberapa aspek seperti tingkat ketajaman, kepekaan warna dan banyak atau tidaknya derau atau noise. Pengolahan citra diperlukan untuk menghasilkan citra digital dengan kualitas yang lebih baik. Penelitian ini bertujuan untuk mengimplementasikan penggunaan metode Mean filtering, Median filtering dan Contra-Harmonic Mean filtering untuk mereduksi Gaussian, Speckle dan Salt & Pepper noise pada citra grayscale pola tenunan beberapa daerah di Provinsi Nusa Tenggara Timur. Pengujian dilakukan dengan menganalisa rata-rata nilai Mean square error (MSE) dan Peak Signal to Noise Ratio (PSNR) disertai dengan pengamatan visual. Nilai MSE dan PSNR berbanding terbalik yang mana citra yang baik memiliki nilai MSE yang paling kecil dan PSNR yang paling besar. Hasil penelitian ini menunjukan bahwa untuk mereduksi gaussian noise ketiga metode memperoleh hasil yang baik dengan nilai PSNR di kisaran 67 dB, untuk mereduksi speckle noise metode Mean filtering dan Contra-Harmonic Mean filtering lebih unggul bila dibandingkan dengan metode Median filtering dengan nilai PSNR di kisaran 77 dB dan untuk mereduksi Salt & pepper noise metode Median filtering lebih unggul bila dibandingkan dengan metode Mean filtering dan Contra-Harmonic Mean filtering dengan nilai PSNR sebesar 86.2846 dB. Kata kunci : mean filtering, median filtering, contra-harmonic mean filtering, gaussian noise, speckle noise, salt & pepper noise
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Edwin, R. Arboleda, C. Fajardo Arnel, and P. Medina Ruji. "Green coffee beans feature extractor using image processing." TELKOMNIKA Telecommunication, Computing, Electronics and Control 18, no. 4 (2020): 2027–34. https://doi.org/10.12928/TELKOMNIKA.v18i4.13968.
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This study offers a novel solution to deal with the low signal-to-noise ratio and slow execution rate of the first derivative edge detection algorithms namely, Roberts, Prewitt and Sobel algorithms. Since the two problems are brought about by the complex mathematical operations being used by the algorithms, these were replaced by a discriminant. The developed discriminant, equivalent to the product of total difference and intensity divided by the normalization values, is based on the “pixel pair formation” that produces optimal peak signal to noise ratio. Results of the study applying the discriminant for the edge detection of green coffee beans shows improvement in terms of peak signal to noise ratio (PSNR), mean square error (MSE), and execution time. It was determined that accuracy level varied according to the total difference of pixel values, intensity, and normalization values. Using the developed edge detection technique led to improvements in the PSNR of 2.091%, 1.16 %, and 2.47% over Sobel, Prewitt, and Roberts respectively. Meanwhile, improvement in the MSE was measured to be 13.06%, 7.48 %, and 15.31% over the three algorithms. Likewise, improvement in execution time was also achieved at values of 69.02%, 67.40 %, and 65.46% over Sobel, Prewitt, and Roberts respectively.
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Farhan, Ahmed, Rezwan us Saleheen, Chen Li Wei, and Farhan Mahbub. "De-noising of an Image using Fuzzy Inference System and Performance Comparison with the Conventional system." Journal of Engineering Advancements 2, no. 03 (2021): 164–68. http://dx.doi.org/10.38032/jea.2021.03.007.
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Noise prevailing in the image can diminish the physical appearance of the objects existing within the image and make them frail. Present research emphasizes a fuzzy inference system eradicating several types of noise from the images. The investigation implies the utilization of different levels of Salt & Pepper noise. Followed by the pixel determination applying a mask, the disparity between the focused pixel's intensity with the minimum, average, and maximum power of the chosen window has been determined. Since two fuzzy valued outputs have been obtained to match them, the one provided by a low noise rate would demonstrate the more accurate filter for the selected window. Utilizing Matlab the Peak Signal-to-Noise ratio (PSNR) and Mean Square Error (MSE) are determined for evaluating the noise reduction performance. However, these values of PSNR and MSE obtained from this research are also compared with the conventional fuzzy filtering system.
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Fialho, Vitor. "Image Transmission Analysis using CSS Modulation Scheme." International Journal of Innovative Technology and Exploring Engineering 12, no. 12 (2023): 32–35. http://dx.doi.org/10.35940/ijitee.l9753.11121223.
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Image transmission through low-speed communication systems has been a challenge to overcome in the last few years. Actual IoT technologies are supported by LPWAN, where power consumption is a primary issue to consider. The image transmission study presented in this paper is based on Chirp Spread Spectrum (CSS) modulation scheme used by LoRa. A simulation model for image transmission is presented, where the communication channel is based on additive white Gaussian noise (AWGN), with a configurable signal-to-noise ratio (SNR). This model allows the modification of several LoRa CSS parameters such as: spreading factor (SF) bandwidth (BW) and code rate (CR). The adopted metrics for the evaluation of the proposed methodology are symbol error rate (SER), bit error rate (BER) and peak signal-to-noise ratio (PSNR). The first two figures of merit allow the study of the transmission quality and with the last one is possible to infer the received image quality. For a SF=8 and SNR=-10 dB the obtained values of SER and BER are 0.001 1e-4, respectively. These values will lead to a PSNR = 21 dB.
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Lakhdar, Moulay, R. Méliani, and M. Kandouci. "Research on unequal error protection with punctured turbo codes in jpeg image transmission system." Serbian Journal of Electrical Engineering 4, no. 1 (2007): 95–100. http://dx.doi.org/10.2298/sjee0701095l.
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An investigation of Unequal Error Protection (UEP) methods applied to JPEG image transmission using turbo codes is presented. The JPEG image is partitioned into two groups, i.e., DC components and AC components according to their respective sensitivity to channel noise. The highly sensitive DC components are better protected with a lower coding rate, while the less sensitive AC components use a higher coding rate. While we use the s-random interleaver and s-random odd-even interleaver combined with odd-even puncturing, we can fix easily the local rate of turbo-code. We propose to modify the design of s-random interleaver to fix the number of parity bits. A new UEP scheme for the Soft Output Viterbi Algorithm (SOVA) is also proposed to improve the performances in terms of Bit Error Rate (BER) and Peak Signal to Noise Ratio (PSNR). Simulation results are given to demonstrate how the UEP schemes outperforms the equal error protection (EEP) scheme in terms of BER and PSNR.
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Aviantoro, Kevin, and Yulia Darnita. "IMPLEMENTASI WIENER, CONTRAST STRETCHING, SHARPENING FILTER PADA CITRA SEMANGKA MENGGUNAKAN MSE,RMSE, DAN PSNR." Djtechno: Jurnal Teknologi Informasi 5, no. 2 (2024): 195–205. http://dx.doi.org/10.46576/djtechno.v5i2.4613.
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Penelitian ini mengkaji tiga metode pemrosesan citra Wiener Filter, Contrast Stretching, dan Sharpening Filter untuk meningkatkan kualitas citra semangka. Evaluasi kinerja dilakukan menggunakan Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), dan Root Mean Square Error (RMSE). Wiener Filter efektif mengurangi noise, Contrast Stretching meningkatkan kontras, dan Sharpening Filter menonjolkan detail. MSE mengukur rata-rata kesalahan kuadrat antara citra asli dan citra yang diproses, dengan nilai < 1 menunjukkan kualitas bagus dan > 1 kualitas kurang bagus. PSNR mengukur rasio sinyal maksimum terhadap noise, dengan nilai < 20 dB menunjukkan kualitas kurang bagus dan > 40 dB kualitas bagus. RMSE, sebagai akar dari MSE, memberikan ukuran kesalahan absolut antara citra asli dan citra yang diproses. Nilai RMSE yang lebih rendah menunjukkan kualitas yang lebih baik dan memudahkan pemahaman besaran kesalahan.
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Motaung, William B., Kingsley A. Ogudo, and Chabalala S. Chabalala. "Optimal Video Compression Parameter Tuning for Digital Video Broadcasting (DVB) using Deep Reinforcement Learning." International Conference on Intelligent and Innovative Computing Applications 2022 (December 31, 2022): 270–76. http://dx.doi.org/10.59200/iconic.2022.030.
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DVB (digital video broadcasting) has undergone an enormous paradigm shift, especially through internet streaming that utilizes multiple channels (i.e., secured hypertext transfer protocols). However, due to the limitations of the current communication network infrastructure, video signals need to be compressed before transmission. Whereas most recent research has concentrated and focused on assessing video quality, little to no study has worked on improving the compression processes of digital video signals in lightweight DVB setups. This study provides a video compression strategy (DRL-VC) that employs deep reinforcement learning for learning the suitable parameters used in digital video signal compression. The problem is formulated as a multi-objective one, considering the structural similarity index metric (SSIM), the delay time, and the peak signal-to-noise ratio (PSNR). Based on the findings of the experiments, our proposed scheme increases bitrate savings while at a constant PSNR. Results also show that our scheme performs better than the benchmarked compression schemes. Finally, the root means square error values show a consistent rate across different video streams, indicating the validity of our proposed compression scheme.
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Hirota, Kaoru, Hajime Nobuhara, Kazuhiko Kawamoto, and Shin’ichi Yoshida. "Image Compression and Reconstruction based on Fuzzy Relation and Soft Computing Technology." Journal of Advanced Computational Intelligence and Intelligent Informatics 8, no. 1 (2004): 72–80. http://dx.doi.org/10.20965/jaciii.2004.p0072.
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A fast image reconstruction method for Image Compression method based on Fuzzy relational equation (ICF) and soft computing is proposed. In experiments using 20 images (Standard Image DataBAse), the decrease in image reconstruction time to 1/132.02 and 1/382.29 are obtained when the compression rate is 0.0156 and 0.0625, respectively, and the proposed method outperforms the conventional one in the Peak Signal to Noise Ratio (PSNR). ICF using nonuniform coders over YUV color space is proposed in order to achieve effective compression. Linear quantization of compressed image data is introduced in order to improve the compression rate. Through experiments using 100 typical images (Corel Gallery, Arizona Directory), PSNR increases at 7.9-14.1% compared with the conventional method under the condition that compression rates are 0.0234-0.0938.
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Kamalin, C. Jenifer, and G. MuthuLakshmi. "A Hybrid BTC Based Compression Techniques of General Images." International Journal of Membrane Science and Technology 10, no. 5 (2023): 878–85. http://dx.doi.org/10.15379/ijmst.v11i1.3587.
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In this paper we propose a new approach for the compression of the general images by combining the Discrete Wavelet Transform (DWT) with Adaptive Block Truncation Coding –Edge Quantization (ABTC- EQ). At the first the standard image is processed by DWT decomposition and into its approximations and details. From this finer and approximation details are separated. The finer details of the image then noted and discarded. The approximate details are noted and further processed in to ABTC-EQ. This approach i.e combination of DWT with AMBTC-EQ gives a better result than other techniques. The Peak Signal to Noise Ratio (PSNR), Weighted Peak Signal to Noise Ratio (WPSNR), Bit Rate (BR), and Structural SIMilarity Index (SSIM) are among the parametric measurements that are used to evaluate image quality. The comparison analysis demonstrates that the suggested algorithm outperforms both BTC and ABTC-EQ.
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I Dewa Gede Hardi Rastama, I Made Oka Widyantara, and Linawati. "Medical Image Compression Techniques with Wavelet Discrete Transformation and Entropy Encoding." Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 4, no. 1 (2020): 155–62. http://dx.doi.org/10.29207/resti.v4i1.1487.
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Medical imaging is a presentment of human organ parts. Medical imaging is saved on a film; therefore, it needs a big saving quota. Compressing is a process to remove redundancy from a piece of information without reducing its quality. This study recommended compressed medical image with DWT (Discrete Wavelet Transform) with adaptive threshold added and entropy copying with the Run Length Encoding (RLE) coding. This study is comparing several parameters, such as compressed ratio and compressed image file size, and PSNR (Peak Signal to Noise Ratio) for analyzing the quality of reconstructive image. The study showed that the comparison of rate, compressed ratio, and PSNR tracing of Haar and Daubechies doesn’t have a significant difference. Comparison of rate, compressed ratio, and PSNR tracing on the hard and soft threshold is the rate of the sold threshold is lower than the hard threshold. The optimal outcome of this study is to use a soft threshold.
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Zhu, Hong Gao, and Qi Feng. "A Video Bit Rate Control Algorithm Based on Weighted Estimate of Image Brightness Difference." Applied Mechanics and Materials 347-350 (August 2013): 844–48. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.844.
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Rate control is the core issue to realize video encoder, and it is also one of the key factors determining the quality of video code system. Given the MAD (Mean Absolute Difference) prediction and the drawback of bit rate control in the BU (Basic Unit) layer, improvements are put forward on the basis of analyzing and researching the G012 rate control algorithms in this paper. In this paper, we proposed a new video bit rate control algorithm to overcome the drawback of bit rate control in the BU (Basic Unit) layer. Combined with the image brightness gradient value to estimate in the MAD prediction, the allocation encoding bits method based on the PSNR (Peak Signal to Noise Ratio) is proposed in the rate control of BU layer. The experiment results show that compared with JM algorithms in H.264 standard reference software, the improved algorithm is enhanced in the PSNR.
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Hasan, Nayeem, Md Saiful Islam, Wenyu Chen, Muhammad Ashad Kabir, and Saad Al-Ahmadi. "Encryption Based Image Watermarking Algorithm in 2DWT-DCT Domains." Sensors 21, no. 16 (2021): 5540. http://dx.doi.org/10.3390/s21165540.
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This paper proposes an encryption-based image watermarking scheme using a combination of second-level discrete wavelet transform (2DWT) and discrete cosine transform (DCT) with an auto extraction feature. The 2DWT has been selected based on the analysis of the trade-off between imperceptibility of the watermark and embedding capacity at various levels of decomposition. DCT operation is applied to the selected area to gather the image coefficients into a single vector using a zig-zig operation. We have utilized the same random bit sequence as the watermark and seed for the embedding zone coefficient. The quality of the reconstructed image was measured according to bit correction rate, peak signal-to-noise ratio (PSNR), and similarity index. Experimental results demonstrated that the proposed scheme is highly robust under different types of image-processing attacks. Several image attacks, e.g., JPEG compression, filtering, noise addition, cropping, sharpening, and bit-plane removal, were examined on watermarked images, and the results of our proposed method outstripped existing methods, especially in terms of the bit correction ratio (100%), which is a measure of bit restoration. The results were also highly satisfactory in terms of the quality of the reconstructed image, which demonstrated high imperceptibility in terms of peak signal-to-noise ratio (PSNR ≥ 40 dB) and structural similarity (SSIM ≥ 0.9) under different image attacks.
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Irwan Jani Tarigan. "Teknik Filter Mean dan Median untuk Perbaikan Citra." Jurnal Armada Informatika 2, no. 1 (2018): 141–47. https://doi.org/10.36520/jai.v2i1.15.
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Gambar semisal foto dan lain sebagainya, bagi sebagian orang adalah kenangan yangmembawa beribu makna. Seperti disebutkan dalam sebuah kata bijak, satu kata hanya berartisatu kata tetapi sebuah gambar mewakili beribu makna. Meski saat sekarang, posisi gambartelah digeser oleh gambar bergerak seperti video, hanya saja penggunaan gambar sebagaimedia penyimpan sebuah peristiwa tetap berada pada posisi yang strategis. Dalam penulisanskripsi ini penulis memilih metode pengurangan derau (reduksi noise) sebagai metodeperbaikan citra. Cara kerja mean filtering dan median filtering tidak tergantung pada nilainilaiyang berbeda dengan nilai-nilai yang umum pada dalam lingkungannya sehingga filter inidapat mempertahankan detail citra asli. Kualitas citra diukur dengan dua besaran, yaitu MSE(Mean Square Error) dan PSNR (Peak Signal to Noise Ratio). MSE (Mean Square Error)menyatakan tingkat kesalahan kuadrat rata-rata dari codebook yang dihasilkan terhadapvektor input. PSNR digunakan untuk menghitung rasio citra keluaran terhadap noise.Dikarenakan beberapa sinyal mempunyai pola data yang berubah-ubah, PSNR biasanyadinyatakan dalam skala dicibel dalam bentuk logaritma. Semakin kecil nilai MSE menunjukkansemakin sesuai dengan vektor input. Parameter PSNR bernilai sebaliknya, semakin besarparameter PSNR semakin bagus codebook yang dihasilkan.
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Ashok, K., A. Kalaiselvi, and V. R. Vijaykumar. "Adaptive impulse detection based selective window median filter for removal of random-valued impulse noise in digital images." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 35, no. 5 (2016): 1604–16. http://dx.doi.org/10.1108/compel-04-2016-0140.
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Purpose One of the fundamental tasks in the field of image processing is image denoising. Images are often corrupted by different types of noise and the restoration of images degraded with random-valued impulse noise is still a challenging task. The paper aims to discuss these issues. Design/methodology/approach This paper presents an adaptive threshold-based impulse noise detection following by a novel selective window median filter for restoration of RVIN pixels. Findings The proposed method emphasis a local image statistics using an exponential nonlinear function with an adaptive threshold is derived from the rank-ordered trimmed median absolute difference (ROTMAD) are deliberated to detect the noisy pixels. In the filtering stage, a selective 3×3 moving window median filter is applied to restore the detected noisy pixel. Originality/value Experimental result shows that the proposed algorithm outperforms the existing state-of-art techniques in terms of noise removal and quantitative metrics such as peak signal to noise ratio (PSNR), mean absolute error (MAE), structural similarity index metric (SSIM) and miss and false detection rate.
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Chen, Qunlin, Derong Chen, Jiulu Gong, and Jie Ruan. "Low-Complexity Rate-Distortion Optimization of Sampling Rate and Bit-Depth for Compressed Sensing of Images." Entropy 22, no. 1 (2020): 125. http://dx.doi.org/10.3390/e22010125.
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Compressed sensing (CS) offers a framework for image acquisition, which has excellent potential in image sampling and compression applications due to the sub-Nyquist sampling rate and low complexity. In engineering practices, the resulting CS samples are quantized by finite bits for transmission. In circumstances where the bit budget for image transmission is constrained, knowing how to choose the sampling rate and the number of bits per measurement (bit-depth) is essential for the quality of CS reconstruction. In this paper, we first present a bit-rate model that considers the compression performance of CS, quantification, and entropy coder. The bit-rate model reveals the relationship between bit rate, sampling rate, and bit-depth. Then, we propose a relative peak signal-to-noise ratio (PSNR) model for evaluating distortion, which reveals the relationship between relative PSNR, sampling rate, and bit-depth. Finally, the optimal sampling rate and bit-depth are determined based on the rate-distortion (RD) criteria with the bit-rate model and the relative PSNR model. The experimental results show that the actual bit rate obtained by the optimized sampling rate and bit-depth is very close to the target bit rate. Compared with the traditional CS coding method with a fixed sampling rate, the proposed method provides better rate-distortion performance, and the additional calculation amount amounts to less than 1%.
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Goyal, Lalit Mohan, Mamta Mittal, Ranjeeta Kaushik, et al. "Improved ECG Watermarking Technique Using Curvelet Transform." Sensors 20, no. 10 (2020): 2941. http://dx.doi.org/10.3390/s20102941.
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Hiding data in electrocardiogram signals are a big challenge due to the embedded information that can hamper the accuracy of disease detection. On the other hand, hiding data into ECG signals provides more security for, and authenticity of, the patient’s data. Some recent studies used non-blind watermarking techniques to embed patient information and data of a patient into ECG signals. However, these techniques are not robust against attacks with noise and show a low performance in terms of parameters such as peak signal to noise ratio (PSNR), normalized correlation (NC), mean square error (MSE), percentage residual difference (PRD), bit error rate (BER), structure similarity index measure (SSIM). In this study, an improved blind ECG-watermarking technique is proposed to embed the information of the patient’s data into the ECG signals using curvelet transform. The Euclidean distance between every two curvelet coefficients was computed to cluster the curvelet coefficients and after this, data were embedded into the selected clusters. This was an improvement not only in terms of extracting a hidden message from the watermarked ECG signals, but also robust against image-processing attacks. Performance metrics of SSIM, NC, PSNR and BER were used to measure the superiority of presented work. KL divergence and PRD were also used to reveal data hiding in curvelet coefficients of ECG without disturbing the original signal. The simulation results also demonstrated that the clustering method in the curvelet domain provided the best performance—even when the hidden messages were large size.
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PURNAMASARI, RITA, and ANDRIYAN BAYU SUKSMONO. "Compressive Sampling untuk Sinyal Beat Radar Cuaca via Discrete Cosine Transform (DCT)." ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika 7, no. 2 (2019): 238. http://dx.doi.org/10.26760/elkomika.v7i2.238.
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ABSTRAKCompressive sampling (CS) merupakan metode baru yang memungkinkan proses pengambilan sampel dan kompresi dilakukan secara bersamaan sehingga dapat mempercepat waktu komputasi sekaligus memperkecil bandwidth saat dilewatkan pada media transmisi. Salah satu cara agar CS dapat bekerja secara optimal adalah jika sinyal yang akan diolah memiliki tingkat sparsitas yang tinggi. Pada makalah ini, mengusulkan algoritma Discrete Cosine Transform (DCT) sebagai metode transformasi sparsitas untuk sinyal beat radar cuaca IWarp. Sinyal beat menjadi sparse setelah direpresentasikan pada domain frekuensi, sehingga dapat mengambil sampelnya secara acak dan akhirnya mendapatkan sekumpulan sinyal sampel yang telah berukuran lebih kecil daripada sinyal beat radar awal. Pada penelitian ini menggunakan ℓ -magic untuk melakukan rekonstruksi dari sinyal yang telah terkompresi tersebut. Simulasi numerik menunjukkan bahwa algoritma yang diusulkan berada pada performansi yang baik dengan rata-rata Peak Signal Noise to Ratio (PSNR) sebesar 15,17 dB.Kata kunci: CS, radar cuaca, sparsitas, DCT, rekonstruksi ℓ ABSTRACTCompressive sampling (CS) is a new method that allows sampling and compression to be carried out simultaneously so that it can increase the computing time and reduce bandwidth while passed on the transmission media. One way for CS to work optimally is if the signal to be processed has a high sparsity level. In this paper we propose the Discrete Cosine Transform (DCT) algorithm as a sparsity transformation method for IWarp weather radar beat signals. The beat signal becomes sparse after being represented in the frequency domain, so this can randomly take samples and finally get a set of sample signals that are smaller than the initial radar beat signal. In this reasearch, use ℓ-magic to reconstruct the compressed signal. Numerical simulations show that the proposed algorithm is in good performance with an average Peak Signal Noise to Ratio (PSNR) of 15.17 dBKeywords: CS, weather radar, sparsity, DCT, ℓ-reconstruction
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Huang, Lin, Zhaoyang Xiang, Jian Li, Heng Yao, and Chuan Qin. "New Framework of Self-Embedding Fragile Watermarking Based on Reference Sharing Mechanism." Security and Communication Networks 2022 (June 25, 2022): 1–14. http://dx.doi.org/10.1155/2022/2699802.
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We proposed in this paper a new self-embedding framework based on a reference sharing mechanism. The framework has high flexibility; it can not only estimate the optimal recovered image quality based on a given tampering rate but also estimate the largest tampering rate that the framework can resist based on the given peak signal-to-noise ratio (PSNR) of the recovered image. When the tampering rate is given, we first calculate the largest number of character bits and then allocate an appropriate number of character bits according to the complexity of the image block to achieve the optimal recovered image quality. When the PSNR of the recovered image is given, the number of character bits is minimized by satisfying the corresponding constraints to achieve the largest tolerable tampering rate. Experimental results show the flexibility, effectiveness, and superiority of the proposed scheme compared with some reported schemes.
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Patel, Dharmeshkumar, and Ninad Bhatt. "Performance Evaluation of Conventional and Neural Network-Based Decoder for an Audio of Low-Girth LDPC Code." Journal of Electrical and Computer Engineering 2023 (October 27, 2023): 1–17. http://dx.doi.org/10.1155/2023/1071142.
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Noise in a communication system degrades the signal level at the receiver, and as a result, the signal is not properly recovered or eliminated at the receiver side. To avoid this, it is necessary to modify the signal before transmission, which is achieved using channel coding. Channel coding provides an opportunity to recover the noisy signal at the receiver side. The low-density parity-check (LDPC) code is an example of a forward error correcting code. It offers near Shannon capacity approaching performance; however, there is a constraint regarding high-girth code design. When the low-girth LDPC code is decoded using conventional methods, an error floor can occur during iterative decoding. To address this issue, a neural network (NN)-based decoder is utilized to overcome the decoding problem associated with low-girth codes. In this work, a neural network-based decoder is developed to decode audio samples of both low- and high-girth LDPC codes. The neural network-based decoder demonstrates superior performance for low-girth codes in terms of bit error rate (BER), peak signal-to-noise-ratio (PSNR), and mean squared error (MSE) with just a single iteration. Audio samples sourced from the NOIZEUS corpus are employed to evaluate the designed neural network. Notably, when compared to a similar decoder, the decoder developed in this study exhibits an improved bit error rate for the same signal-to-noise ratio.
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Khanbari, Shada Omer, and Adel Sallam M. Haider. "Enhanced Mammography image for Breast cancer detection using LC-CLAHE technique." University of Aden Journal of Natural and Applied Sciences 24, no. 1 (2022): 143–54. http://dx.doi.org/10.47372/uajnas.2020.n1.a12.
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Breast cancer is the greatest challenging health complexities that medical science is facing. Most cases can be prevented by early detection and diagnosis which are the best way to cure breast cancer to decrease the mortality rate. The aim of this research is to obtain a method for enhancing the mammography images by using the proposed method which is incorporating the Local Contrast with Contrast Limited Adaptive Histogram Equalization (LC-CLAHE) to improve the appearance and to increase the contrast of the image and then de-noised by 2D wiener filter techniques. To extract the region of interest (tumor), we used region growing technique for the segmentation process. The standard Mammographic Image Analysis Society (MIAS) database images are considered for the evaluation. Efficiency is measured by Root Mean Square Error (RMSE) and Peak Signal to Noise Ratio (PSNR). It is observed that the proposed method with wiener filter gives higher (PSNR) and lower (RMSE), with a significant filter mask [3 3].
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Yang, Rui, and Dahai Li. "Adaptive wavelet transform based on artificial fish swarm optimization and fuzzy C-means method for noisy image segmentation." Computer Science and Information Systems, no. 00 (2022): 39. http://dx.doi.org/10.2298/csis220321039y.
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Aiming at the problem that traditional fuzzy C-means (FCM) clustering algorithm is susceptible to noise in processing noisy images, a noisy image segmentation method based on FCM wavelet domain feature enhancement is proposed. Firstly, the noise image is decomposed by two-dimensional wavelet. Secondly, the edge enhancement of the approximate coefficient is carried out, and the artificial fish swarm (AFS) optimization algorithm is used to process the threshold value of the detail coefficient, and the processed coefficient is reconstructed by wavelet transform. Finally, the reconstructed image is segmented by FCM algorithm. Five typical gray-scale images are selected by adding Gaussian noise and Salt& pepper noise, respectively, and segmented by various methods. The peak signal-to-noise ratio (PSNR) and error rate (MR) of segmented images are used as performance indexes. Experimental results show that compared with traditional FCM clustering algorithm segmentation method, particle swarm optimization (PSO) segmentation method and other methods, the indexes of image segmentation by the proposed method is greatly improved. It can be seen that the proposed segmentation method retains the texture information of image edge well, and its anti-noise performance and segmentation performance are improved.
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Efe, Enes. "High-fidelity steganography in EEG signals using advanced transform-based methods." PeerJ Computer Science 11 (May 26, 2025): e2900. https://doi.org/10.7717/peerj-cs.2900.
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The increasing prevalence of digital health solutions and smart health devices (SHDs) ensures the continuity of personal biometric data while simultaneously raising concerns about their security and privacy. Consequently, the development of novel encryption techniques and data protection policies is crucial to comply with regulations such as The Health Insurance Portability and Accountability Act (HIPAA) and to safeguard against cyber threats. This study introduces a robust and efficient method for embedding private information into electroencephalogram (EEG) signals by employing the stationary wavelet transform (SWT), singular value decomposition (SVD), and tent map techniques. The proposed approach aims to increase embedding capacity while maintaining signal integrity, ensuring resilience against various forms of distortion, and achieving computational efficiency. Experiments were conducted on three publicly available EEG datasets (Graz A, DEAP, and Bonn), and performance was evaluated using widely recognized metrics, including peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), percentage root mean square difference (PRD), normalized cross-correlation (NCC), bit error rate (BER), and Euclidean distance (ED). The results indicate that the method preserves perceptual quality, achieving PSNR values above 60 dB and demonstrating minimal signal distortion. Robustness tests involving noise addition, random cropping, and low-pass filtering confirm the method’s high resilience, with BER approaching zero and NCC near unity. Moreover, the proposed method demonstrates significantly reduced hiding and extraction times compared to conventional approaches, enhancing its suitability for real-time, secure biomedical data transmission.
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Xie, Yipeng, Mingwei Lei, Jianquan Zhang, Wenbo Dong, and Meng Shi. "Low-Frequency Communication Based on Rydberg-Atom Receiver." Electronics 14, no. 5 (2025): 1041. https://doi.org/10.3390/electronics14051041.
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Rydberg-atom receivers have developed rapidly with increasing sensitivity. However, studies on their application in low-frequency electric fields remain limited. In this work, we demonstrate low-frequency communication using an electrode-embedded atom cell and a whip antenna without the need for a low-noise amplifier (LNA). Three modulations—binary phase-shift keying (BPSK), on–off keying (OOK), and two-frequency shift keying (2FSK)—were employed for communication using a Rydberg-atom receiver operating near 100 kHz. The signal-to-noise ratio (SNR) of the modulated low-frequency signal received by Rydberg atoms was measured at various emission voltages. Additionally, we demonstrated the in-phase and quadrature (IQ) constellation diagram, error vector magnitude (EVM), and eye diagram of the demodulated signal at different symbol rates. The EVM values were measured to be 8.8% at a symbol rate of 2 kbps, 9.4% at 4 kbps, and 13.7% at 8 kbps. The high-fidelity digital color image transmission achieved a peak signal-to-noise ratio (PSNR) of 70 dB. Our results demonstrate the feasibility of a Rydberg-atom receiver for low-frequency communication applications.
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Fadhlurrahman, Rafi, Sevada Afta Wijaksana, Farhan Ibnu Prabowo, and Reni Rahmadewi. "PERBANDINGAN EDGE DETECTION METODE LAPLACIAN OF GAUSSIAN DAN CANNY PADA CITRA CT SCAN MENGGUNAKAN SOFTWARE MATLAB." JATI (Jurnal Mahasiswa Teknik Informatika) 9, no. 3 (2025): 4024–31. https://doi.org/10.36040/jati.v9i3.13455.
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Edge detection merupakan sebuah proses identifikasi titik-titik perubahan intensitas yang signifikan dalam sebuah citra. Dalam bidang medis, deteksi tepi sangat penting untuk memudahkan proses segmentasi serta analisis dan diagnosis, salah satunya pada citra Computed Tomography (CT) scan yang seringkali menghadapi masalah noise. Oleh karena itu, diperlukan analisis perbandingan untuk menentukan metode deteksi tepi yang tepat guna meningkatkan efektivitas dalam identifikasi citra hasil scan. Penelitian ini bertujuan untuk membandingkan dua metode deteksi tepi, yaitu Laplacian of Gaussian (LoG) dan Canny, dengan citra CT scan paru-paru sebagai sampel. Tahapan penelitian dimulai dengan pemilihan dataset citra CT scan paru-paru, dilanjutkan dengan pra-pemrosesan citra yang mencakup grayscaling, resizing, dan smoothing menggunakan filter Gaussian. Selanjutnya, dilakukan implementasi kdeua metode deteksi tepi menggunakan software MATLAB. Evaluasi dilakukan berdasarkan nilai Mean Squared Error (MSE) dan Peak Signal-to-Noise Ratio (PSNR) serta melalui visualisasi hasil. Hasil penelitian menunjukkan bahwa metode Canny memberikan deteksi tepi yang lebih halus dengan noise yang lebih rendah dengan rata-rata pengukuran MSE sebesar 2129.08, dan rata-rata PSNR sebesar 15.30 dB. Sementara metode LoG menghasilkan lebih banyak detail tepi, tetapi dengan noise yang lebih tinggi dengan rata-rata pengukuran MSE sebesar 4517.60 dan rata-rata PSNR sebesar 11.28 dB.
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Lin, Wen-Yen, Tin-Hao Chang, and Shu-Ming Tseng. "Deep Learning-Based Cross-Layer Power Allocation for Downlink Cell-Free Massive Multiple-Input–Multiple-Output Video Communication Systems." Symmetry 15, no. 11 (2023): 1968. http://dx.doi.org/10.3390/sym15111968.
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We propose a deep learning-based cross-layer power allocation method for asymmetric cell-free massive MIMO video communication systems. The proposed cross-layer approach considers physical layer channel state information (CSI) and the application layer rate distortion (RD) function, and it aims to enhance video quality in terms of peak signal-to-noise ratio (PSNR). Our study develops a decentralized deep neural network (DNN) model to capture intricate system patterns, enabling accurate and efficient power allocation decisions. The proposed cross-layer approach includes unsupervised and hybrid (supervised/unsupervised) learning models. The numerical results show that the hybrid method achieves convergence with just 50% of the iterations required by the unsupervised learning model and that it achieves a 1 dB gain in PSNR over the baseline physical layer scheme.
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Pereira, Fábio Henrique, Elesandro Antonio Baptista, Nivaldo Lemos Coppini, Rafael Do Espírito-Santo, and Ademir João de Oliveira. "Low-loss image compression techniques for cutting tool images: a comparative study of compression quality measures." Exacta 8, no. 2 (2010): 225–35. http://dx.doi.org/10.5585/exacta.v8i2.2000.
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This work accomplishes a comparative study between two distinct image compression techniques, namely the Lifting technique and the Principal Components Analysis (PCA), in order to determine what of these two approaches is more appropriate for cutting tool wear images analysis. Lifting and Principal Components Analysis were applied in original images of a cutting tool for producing a low resolution version, while keeping the more important details of the image. The low-loss image compression quality provided by these techniques was expressed in terms of the compression factor (ρ), the Mean Square Error (MSE) and the Peak Signal-to-Noise Rate (PSNR) provided by the image compression process. The tests were accomplished using the high-performance language for technical computing MATLAB®, and the results shown that the PCA technique presented the best values of PSNR with low compression rates. However, with high values of compression rates the lifting technique gave the highest PSNR.
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Pereira, Fábio Henrique, Elesandro Antonio Baptista, Nivaldo Lemos Coppini, Rafael Do Espírito-Santo, and Ademir João de Oliveira. "Low-loss image compression techniques for cutting tool images: a comparative study of compression quality measures DOI: 10.5585/exacta.v8i2.2000." Exacta 8, no. 2 (2010): 225–35. http://dx.doi.org/10.5585/exactaep.v8i2.2000.
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This work accomplishes a comparative study between two distinct image compression techniques, namely the Lifting technique and the Principal Components Analysis (PCA), in order to determine what of these two approaches is more appropriate for cutting tool wear images analysis. Lifting and Principal Components Analysis were applied in original images of a cutting tool for producing a low resolution version, while keeping the more important details of the image. The low-loss image compression quality provided by these techniques was expressed in terms of the compression factor (ρ), the Mean Square Error (MSE) and the Peak Signal-to-Noise Rate (PSNR) provided by the image compression process. The tests were accomplished using the high-performance language for technical computing MATLAB®, and the results shown that the PCA technique presented the best values of PSNR with low compression rates. However, with high values of compression rates the lifting technique gave the highest PSNR.
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Mulyono, Ibnu Utomo Wahyu, Yupie Kusumawati, and Novita Kurnia Ningrum. "Analisa Visual Citra Hasil Kombinasi Steganografi dan Kriptografi Berbasis Least Significant Bit Dalam Cipher." JURNAL MASYARAKAT INFORMATIKA 14, no. 1 (2023): 16–28. http://dx.doi.org/10.14710/jmasif.14.1.51484.
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Kriptografi dan steganografi adalah teknik yang digunakan untuk mengamankan data untuk meminimalkan pencurian data dan akses oleh orang yang tidak berwenang. Kombinasi Rivest Cipher 4 - Least Significant Bit diusulkan dalam penelitian ini untuk memberikan perlindungan bagi pesan dan berbagai format file yang tertanam dalam gambar digital. Pesan rahasia dienkripsi dengan metode RC4 sebelum dimasukkan kedalam gambar menggunakan LSB. Studi ini juga menganalisis kinerja kombinasi algoritma LSB – RC4 pada berbagai file dan ukuran gambar sampul. Gambar sampul menggunakan gambar dengan saluran RGB. Untuk pengukuran kinerja imperceptibilitas digunakan Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), dan analisis histogram.Nilai rata – rata PSNR yang didapatkan pada penelitian ini lebih dari 30 dB, ini membuktikan bahwa kualitas gambar stego sangat baik dan kualitas gambar stego yang baik memiliki nilai PSNR minimal 30 dB. Nilai PSNR yang didapatkan secara keseluruhan lebih dari 30 dB dengan nilai terendahnya 45,15 dB dengan ukuran citra 128x128 pixel.
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Kesrarat, Darun, Vorapoj Patanavijit, Kanabadee Srisomboon, Wilaiporn Lee, and Kornkamol Thakulsukanant. "A Pervasive Numerical Investigation of HDF Discrimination for Identifying and Enhancing Impulsive Noise Photograph." Journal of Lifestyle and SDGs Review 5, no. 3 (2025): e03239. https://doi.org/10.47172/2965-730x.sdgsreview.v5.n03.pe03239.
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Objective: This study aims to investigate the optimal cluster size and the optimal HDT parameter of the noise elimination approach founded on HDT (Hard Decision Threshold) discrimination on a lot total of experimental photographs on CTII for maximum capability. Theoretical Framework: The theoretical framework is founded on the dissimilarity values of the cluster pixels are significantly different neighborhood pixels. However, the capability of the noise elimination approach founded on HDT ultimately depends on the optimal cluster size and the optimal HDT parameter. Method: The noise elimination approach founded on HDT is investigated in both quantitative (in PSNR or Peak Signal to Noise Ratio) and qualitative (visionary). This experiment investigates on a lot of photographs (Lena, Pepper and Pentagon) in CTII (Constant Tension Impulsive Irregularity) at uniform distribution and cluster distribution. Results and Discussion: First, the results of the study based on HDT parameters from Lena, Pepper and Pentagon shows that the optimal HDT parameter is 0.2±0.1 approximately. Next, from numerical outcome on a lot of photographs, the HDT noise elimination approach is capable of the remarkable quality photographs with the first-rate PSNR opposed with former reputable approaches for example Gaussian/Mean filter (MF), Median filter (SMF) and Adaptive Median filter (AMF) for wholly CTII.
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Kumar, Manish, Sudhansu Kumar Mishra, Sumit Kumar Choubey, Sanjay Shankar Tripathy, Dilip Kumar Choubey, and Dinesh Das. "Cat Swarm Optimization based Functional Link Multilayer Perceptron for Suppression of Gaussian and Impulse Noise from Computed Tomography Images." Current Medical Imaging Formerly Current Medical Imaging Reviews 16, no. 4 (2020): 329–39. http://dx.doi.org/10.2174/1573405614666180903115336.
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Background: The Gaussian and impulse noises corrupt the Computed Tomography (CT) images either individually or collectively, and the conventional fixed filters do not have the potential to suppress these noise. Objectives: These spurious noises affect the inherent features of CT image awkwardly. Hence, to handle such a situation adaptive Cat Swarm Optimization based Functional Link Multilayer Perceptron (CSO-FLMLP) has been proposed in this paper to get rid of unwanted noise from the CT images. Methods: Here, the nature-inspired CSO technique which is an optimization algorithm has been employed to assist in updating the weights of FLMLP network. In this work, the cost function considered for CSO is the error between noisy and contextual pixels of reference images which need to minimize. For examining the efficiency of CSO-FLMLP filter, it is compared with the other six competitive adaptive filters. Results: The performance of proposed approach and other state-of-the-art filters are compared on the basis of performance metrics like the structural similarity index (SSIM), peak signal to noise ratio (PSNR), computational time and convergence rate. Supremacy of CSO-FLMLP among the considered adaptive filters is validated through Friedman statistical test. Conclusion: The CSO-FLMLP adaptive filter could successfully re-move the dominant Gaussian, impulse or combination of both noises from the clinical CT images.
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Idbeaa, Tarik, Kasmiran Jumari, Salina Abd. Samad, Ali Abdulgader, and Nidal Eshah. "New Approach of Encrypting Embedded Data in H.264 Compressed Video." Advanced Materials Research 230-232 (May 2011): 346–51. http://dx.doi.org/10.4028/www.scientific.net/amr.230-232.346.
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Digital video steganography has attracted a great deal of research interest in the recent few years in applications. In this paper, we propose a method to embed and encrypt messages into video sequences by using steganography technique Based on the H.264 video coding standard. The system implemented in this work provides robust H.264 video compression constant, without significantly affecting the overall bit rate and quality of the video stream. The results indicate that the algorithm can be implemented steganography fast and efficiently and effect vision and peak signal to noise ratio (PSNR) of video sequences are almost unaffected after decoding.
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Zouggaret, Abdelhak, Mokhtar Besseghier, Youcef Islam Djilani Kobibi, Hocine Abdelhak Azzeddine, and Samir Ghouali. "Medical images transmission over MC-MC-CDMA based MRC detection." STUDIES IN ENGINEERING AND EXACT SCIENCES 5, no. 3 (2024): e12478. https://doi.org/10.54021/seesv5n3-033.
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The increasing demand for high data rate multimedia transmission in wireless networks necessitates robust and spectrally efficient technologies. Multi-code multi-carrier code division multiple access (MC-MC-CDMA) presents a promising solution by combining the advantages of multi-code CDMA and multi-carrier CDMA techniques. This paper comprehensively investigates the MC-MC-CDMA system for medical image transmission applications. A detailed system model is developed, including the transmitter, channel, and maximum ratio combining (MRC) receiver. Analytical expressions for the bit error rate (BER) performance are derived, and comparative studies demonstrate the superior BER performance of MC-MC-CDMA over multi-carrier CDMA and multi-code CDMA systems under varying system parameters. The highlight of this work is the evaluation of the MC-MC-CDMA system for transmitting medical images using MRC detection. Extensive simulations are conducted to analyze the peak signal-to-noise ratio (PSNR) as a measure of received image quality under different signal-to-noise ratio (SNR) conditions. The results reveal that the proposed MC-MC-CDMA system with MRC detection achieves significantly improved PSNR performance compared to equal gain combining (EGC) receivers, enabling reliable and high-quality medical image transmission. The findings underscore the potential of the MC-MC-CDMA system for robust and efficient multimedia data delivery in future wireless healthcare and telemedicine applications.
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Jin, Wangyan, Ling Dai, Liuyan Ge, et al. "Wavelet Transform Image Enhancement Algorithm-Based Evaluation of Lung Recruitment Effect and Nursing of Acute Respiratory Distress Syndrome by Ultrasound Image." Journal of Healthcare Engineering 2021 (September 10, 2021): 1–9. http://dx.doi.org/10.1155/2021/8960465.
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This study aimed to analyze the application of ultrasound images of lung recruitment (LR) nursing treatment guided by positive-end expiratory pressure (PEEP) in patients with acute respiratory distress syndrome (ARDS). An ultrasound image enhancement algorithm (UIEA) wavelet transform (WT) was constructed, and the soft threshold (ST) and adjacent region average (ARA) were introduced for simulation comparison. In addition, the signal-to-noise ratio (SNR), peak signal-to-noise ratio (PSNR), and running time were undertaken as the evaluation indexes. The WT algorithm was applied to the ultrasound images of 85 ARDS patients before and after PEEP recruitment. The mean artery pressure (MAP), heart rate (HR), and central venous pressure (CVP), peak inspiratory pressure (Ppeak), mean inspiratory pressure (Pmean), dynamic lung compliance (DLC), PCO2, and PaO2/FiO2 of the patients were recorded before and after the LR. The results showed that the signal-to-noise ratio (SNR) (19.67 ± 3.15 dB) and PSNR (23.08 ± 2.08 dB) of the images enhanced by the WT algorithm were much higher than those of ST (13.88 ± 2.74 dB and 14.62 ± 1.76 dB, respectively) and ARA (14.96 ± 3.06 dB and 15.11 ± 1.94 dB, respectively), while the running time was in adverse ( P < 0.05 ); the HR and CVP of patients after LR nursing treatment were increased greatly, while the MAP was in the opposite case ( P < 0.05 ); after LR nursing treatment, Ppeak, Pmean, DLC, PCO2, and PaO2/FiO2 of the patient were significantly greater than those before the LR, and the difference was statistically significant ( P < 0.05 ). In short, the WT algorithm not only enhanced the quality of ultrasound images but also shortened the running time and improved the processing efficiency. PEEP LR nursing treatment could effectively improve the vascular patency, cardiac ejection capacity, and DLC in patients with ARDS, thereby increasing the airway pressure and maintaining the unobstructed expiration.
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Kuznetsov, Alexandr, Alexander Onikiychuk, Olga Peshkova, Tomasz Gancarczyk, Kornel Warwas, and Ruslana Ziubina. "Direct Spread Spectrum Technology for Data Hiding in Audio." Sensors 22, no. 9 (2022): 3115. http://dx.doi.org/10.3390/s22093115.
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Direct spread spectrum technology is traditionally used in radio communication systems with multiple access, for example, in CDMA standards, in global satellite navigation systems, in Wi-Fi network wireless protocols, etc. It ensures high security and reliability of information transfer. In addition, spread spectrum technology provides the transmitted signals with a noise-like appearance, thus hiding the semantic content of the messages. We researched this technology for other implementations. The purpose of our study was to investigate new technologies for hiding data in multimedia files. In particular, we investigated the direct spread spectrum in the context of the development of methods for hiding data in audio containers. We considered various spreading sequences (chip codes) and also explored their use for hiding information in audio files. We conducted experimental studies and estimated the bit error rate (BER) in the recovered data. The article also evaluates the distortion of an audio container by the peak signal-to-noise ratio (PSNR). The results of our research enable us to find out which method of forming chip codes gives a lower BER with equal PSNR. We provide recommendations on the formation of spreading sequences to reliably and safely hide informational messages in audio files.
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Chen, Shanshan, Bensheng Qiu, Feng Zhao, Chao Li, and Hongwei Du. "Fast Compressed Sensing MRI Based on Complex Double-Density Dual-Tree Discrete Wavelet Transform." International Journal of Biomedical Imaging 2017 (2017): 1–13. http://dx.doi.org/10.1155/2017/9604178.
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Compressed sensing (CS) has been applied to accelerate magnetic resonance imaging (MRI) for many years. Due to the lack of translation invariance of the wavelet basis, undersampled MRI reconstruction based on discrete wavelet transform may result in serious artifacts. In this paper, we propose a CS-based reconstruction scheme, which combines complex double-density dual-tree discrete wavelet transform (CDDDT-DWT) with fast iterative shrinkage/soft thresholding algorithm (FISTA) to efficiently reduce such visual artifacts. The CDDDT-DWT has the characteristics of shift invariance, high degree, and a good directional selectivity. In addition, FISTA has an excellent convergence rate, and the design of FISTA is simple. Compared with conventional CS-based reconstruction methods, the experimental results demonstrate that this novel approach achieves higher peak signal-to-noise ratio (PSNR), larger signal-to-noise ratio (SNR), better structural similarity index (SSIM), and lower relative error.
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Virk, Amardeep Singh, Mandeep Kaur, and Lovely Passrija. "Performance Evaluation of Image Enhancement Techniques in Spatial and Wavelet Domains." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 3, no. 1 (2012): 162–66. http://dx.doi.org/10.24297/ijct.v3i1c.2771.
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Denoising is one of the important tasks in image processing. Despite the significant research conducted on this topic, the development of efficient denoising methods is still a compelling challenge. In this paper, spatial domain methods and Wavelet Domain Methods of image denoising have been evaluated. The medical ultrasound images suffer from speckle noise which is multiplicative in nature and more difficult to remove than additive noise. In the spatial filter methods Median Filter and Wiener Filter are implemented. These methods are based on the simple formulas that are proposed by different authors. In Wavelet Methods Visu Shrink, Neigh shrink and Bayes Shrink are implemented. The basic idea of wavelet methods is to denoise the image by applying wavelet transform to the noisy image, then thresholding the detailed wavelet coefficient and inverse transforming the set of thresholded coefficient to obtain the denoised image. The comparison of all filters methods is done using various Quality Metrics like Peak Signal-to-Noise Ratio (PSNR), Bit Error Rate (BER), Mean Square Error, etc. The filters methods implemented in MATLAB 7.10.0.499(R2010a).
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Battista, Stefano, Massimo Conti, and Simone Orcioni. "Methodology for Modeling and Comparing Video Codecs: HEVC, EVC, and VVC." Electronics 9, no. 10 (2020): 1579. http://dx.doi.org/10.3390/electronics9101579.
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Online videos are the major source of internet traffic, and are about to become the largest majority. Increasing effort is aimed to developing more efficient video codecs. In order to compare existing and novel video codecs, this paper presents a simple but effective methodology to model their performance in terms of Rate Distortion (RD). A linear RD model in the dB variables, Peak Signal-to-Noise Ratio (PSNR) and Bitrate (BR), easily allows us to estimate the difference in PSNR or BR between two sets of encoding conditions. Six sequences from the MPEG test set with the same resolution, encoded at different BR and different Quantization Parameters, were used to create the data set to estimate each RD model. Three codecs (HEVC, EVC, and VVC) were compared with this methodology, after estimating their models. Fitting properties of each model and a performance comparison between the models are finally shown and discussed.
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Wang, Bin, Yingjie Xie, Shihua Zhou, Changjun Zhou, and Xuedong Zheng. "Reversible Data Hiding Based on DNA Computing." Computational Intelligence and Neuroscience 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/7276084.
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Biocomputing, especially DNA, computing has got great development. It is widely used in information security. In this paper, a novel algorithm of reversible data hiding based on DNA computing is proposed. Inspired by the algorithm of histogram modification, which is a classical algorithm for reversible data hiding, we combine it with DNA computing to realize this algorithm based on biological technology. Compared with previous results, our experimental results have significantly improved the ER (Embedding Rate). Furthermore, some PSNR (peak signal-to-noise ratios) of test images are also improved. Experimental results show that it is suitable for protecting the copyright of cover image in DNA-based information security.
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Kuznetsov, A. A., O. A. Smirnov, A. S. Kiian, and T. Y. Kuznetsova. "Data hiding based on noise-like signal addressing." Radiotekhnika, no. 203 (December 23, 2020): 38–49. http://dx.doi.org/10.30837/rt.2020.4.203.04.
Full textAbstract:
There are various computing techniques (methods) to transmit secret messages. For example, cryptographic techniques hide the semantic content of transmitted messages, presenting them in the form of noise-like minor data. Steganographic techniques hide the existence of information messages itself. In this case, messages are hidden inside cover files, i.e., redundant data that are transmitted in an open way and do not cause suspicion in anyone. An outside observer can intercept cover files, analyze and examine them. However, it is very difficult or even impossible to detect and recover hidden data. This article discusses the techniques for hiding data in cover images using direct spread spectrum. We propose a new technique that consists in direct addressing of pseudo-random sequences. On the one hand, it significantly reduces cover file distortion. On the other hand, the error rate in recovered messages does not increase. Our experiments have shown, that Spread Spectrum Steganography technique indeed reduce the distortion in cover images compared to other techniques. We give some illustrative examples and show the advantages of the proposed method. Even with a significant increase in encoding density, the quality of cover images does not degrade. We also conduct experiments and evaluate image quality based on Mean Squared Error (MSE) and Peak Signal-to-Noise Ratio (PSNR). The obtained results of experimental studies confirm the adequacy and reliability of the research results. The main disadvantage of the proposed data hiding technique is a high computational complexity. To recover messages, it is necessary to calculate sequentially the correlation coefficients with a large number of pseudo-random sequences.
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Tiwari, Archana, and Manisha Sharma. "An Image Authentication Algorithm Using Combined Approach of Watermarking and Vector Quantization." Journal of Intelligent Systems 27, no. 1 (2018): 31–45. http://dx.doi.org/10.1515/jisys-2017-0026.
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Abstract This paper presents a two-stage watermarking technique for image authentication adapting the advantages of vector quantization (VQ). In the proposed algorithm, robust watermark and semifragile watermark are embedded independently in two successive stages. Robust watermark and VQ enhance the security of the system by providing double protection to the designed system, while semifragile watermark helps in authenticating the received image. Watermarks of varying sizes are embedded in the cover image, and their performance is measured in terms of peak signal-to-noise ratio (PSNR), weighted PSNR, and bit error rate. A threshold-based approach is suggested for identification of attacks as acceptable or malicious. The experimental results demonstrate the capabilities of the method in classifying attacks and correctly locating the tampered area. It is possible to detect and determine tampering with very high sensitivity. The present scheme outperforms previous algorithms in terms of imperceptibility, attack classification criteria, robustness feature, and tamper detection feature.
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Mahmoud, Rashad, Elhadad Ahmed, and El-Saady Kamal. "A blind steganography approach for hiding privacy details in images of digital imaging and communications in medicine using QR code." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 4 (2022): 3721–29. https://doi.org/10.11591/ijece.v12i4.pp3721-3729.
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This study aims to hide patient’s privacy details of digital imaging and communications in medicine (DICOM) files using the quick response (QR) code images with the same size using steganographic technique. The proposed method is based on the properties of the discrete cosine transform (DCT) of the DICOM images to embed a QR code image. The proposed method includes two parts: data embedding and extraction process. Moreover, the stego DICOM image could be blindly used to produce the embedded QR code image without the existence of the original DICOM image. The performances of proposed method were evaluated using the metrics of the peak signal to noise ratio (PSNR), the structural similarity index (SSIM), the universal quality index (UQI), the correlation coefficient (R) and the bit error rate (BER) values. The experimental results scored a high PSNR after the embedding process by embedding a QR code image into the DICOM image with the same size.