Relevant bibliographies by topics / Peak signal noise ratio PSNR

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Peak signal noise ratio PSNR'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Peak signal noise ratio PSNR"

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J.S., Ashwin, and Manoharan N. "Audio Denoising Based on Short Time Fourier Transform." Indonesian Journal of Electrical Engineering and Computer Science 9, no. 1 (2018): 89–92. https://doi.org/10.11591/ijeecs.v9.i1.pp89-92.

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This paper presents a novel audio de-noising scheme in a given speech signal. The recovery of original from the communication channel without any noise is a difficult task. Many de-noising techniques have been proposed for the removal of noises from a digital signal. In this paper, an audio denoising technique based on Short Time Fourier Transform (STFT) is implemented. The proposed architecture uses a novel approach to estimate environmental noise from speech adaptively. Here original speech signals are given as input signal. Using AWGN, noises are added to the signal. Then noised signals are
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S. Ashwin, J., and N. Manoharan. "Audio Denoising Based on Short Time Fourier Transform." Indonesian Journal of Electrical Engineering and Computer Science 9, no. 1 (2018): 89. http://dx.doi.org/10.11591/ijeecs.v9.i1.pp89-92.

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<p>This paper presents a novel audio de-noising scheme in a given speech signal. The recovery of original from the communication channel without any noise is a difficult task. Many de-noising techniques have been proposed for the removal of noises from a digital signal. In this paper, an audio de-noising technique based on Short Time Fourier Transform (STFT) is implemented. The proposed architecture uses a novel approach to estimate environmental noise from speech adaptively. Here original speech signals are given as input signal. Using AWGN, noises are added to the signal. Then noised s
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C, Shraddha, Chayadevi M L, Anusuya M A, and Vani H Y. "Enhancing Noise Reduction with Bionic Wavelet and Adaptive Filtering." Inteligencia Artificial 27, no. 74 (2024): 214–26. http://dx.doi.org/10.4114/intartif.vol27iss74pp214-226.

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Speech signals often contain different forms of background and environmental noise. For the development of an efficient speech recognition system, it is essential to preprocess noisy speech signals to reduce the impact of these disturbances. Notably, prior research has paid limited attention to pink and babble noises. This gap in knowledge inspired us to develop and implement hybrid algorithms tailored to handle these specific noise types. We introduce a hybrid method that combines the Bionic Wavelet transform with Adaptive Filtering to enhance signal strength. The performance of this method i
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Kwon, Ju Hyeok, So Eui Kim, Na Hye Kim, Eui Chul Lee, and Jee Hang Lee. "Preeminently Robust Neural PPG Denoiser." Sensors 22, no. 6 (2022): 2082. http://dx.doi.org/10.3390/s22062082.

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Photoplethysmography (PPG) is a simple and cost-efficient technique that effectively measures cardiovascular response by detecting blood volume changes in a noninvasive manner. A practical challenge in the use of PPGs in real-world applications is noise reduction. PPG signals are likely to be compromised by various types of noise, such as scattering or motion artifacts, and removing such compounding noises using a monotonous method is not easy. To this end, this paper proposes a neural PPG denoiser that can robustly remove multiple types of noise from a PPG signal. By casting the noise reducti
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Malleswari, Pinjala N., Ch Hima Bindu, and K. Satya Prasad. "An Improved Denoising of Electrocardiogram Signals Based on Wavelet Thresholding." Journal of Biomimetics, Biomaterials and Biomedical Engineering 51 (June 14, 2021): 117–29. http://dx.doi.org/10.4028/www.scientific.net/jbbbe.51.117.

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Electrocardiogram (ECG) is the most important signal in the biomedical field for the diagnosis of Cardiac Arrhythmia (CA). ECG signal often interrupted with various noises due to non-stationary nature which leads to poor diagnosis. Denoising process helps the physicians for accurate decision making in treatment. In many papers various noise elimination techniques are tried to enhance the signal quality. In this paper a novel hybrid denoising technique using EMD-DWT for the removal of various noises such as Additive White Gaussian Noise (AWGN), Baseline Wander (BW) noise, Power Line Interferenc
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Sonali, Malviya, and Anshuj Jain Prof. "Analysis PSNR of High Density Salt and Pepper Impulse Noise Using Median Filter." International Journal of Trend in Scientific Research and Development 3, no. 1 (2018): 866–70. https://doi.org/10.31142/ijtsrd19086.

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In this paper a new method for the enhancement of gray scale images is introduced, when images are corrupted by fixed valued impulse noise salt and pepper noise . The proposed methodology ensures a better output for low and medium density of fixed value impulse noise as compare to the other famous filters like Standard Median Filter SMF , Decision Based Median Filter DBMF and Modified Decision Based Median Filter MDBMF etc. The main objective of the proposed method was to improve peak signal to noise ratio PSNR , visual perception and reduction in blurring of image. The proposed algorithm repl
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Mardiah, Ainil, Sri Hartati, and Agus Sihabuddin. "Face Image Generation and Enhancement Using Conditional Generative Adversarial Network." IJCCS (Indonesian Journal of Computing and Cybernetics Systems) 16, no. 1 (2022): 1. http://dx.doi.org/10.22146/ijccs.58327.

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The accuracy and speed of a single image super-resolution using a convolutional neural network is often a problem in improving finer texture details when using large enhancement factors. Some recent studies have focused on minimal mean square error, resulting in a high peak signal to noise ratio. Generally, although the peak signal to noise ratio has a high value, the output image is less detailed. This shows that the determination of super-resolution is not optimal. Conditional Generative Adversarial Network based on Boundary Equilibrium Generative Adversarial Network, by combining Mean Squar
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Rao*, G. Manmadha, Raidu Babu D.N, Krishna Kanth P.S.L, Vinay B., and Nikhil V. "Reduction of Impulsive Noise from Speech and Audio Signals by using Sd-Rom Algorithm." International Journal of Recent Technology and Engineering 10, no. 1 (2021): 265–68. http://dx.doi.org/10.35940/ijrte.a5943.0510121.

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Removal of noise is the heart for speech and audio signal processing. Impulse noise is one of the most important noise which corrupts different parts in speech and audio signals. To remove this type of noise from speech and audio signals the technique proposed in this work is signal dependent rank order mean (SD-ROM) method in recursive version. This technique is used to replace the impulse noise samples based on the neighbouring samples. It detects the impulse noise samples based on the rank ordered differences with threshold values. This technique doesn’t change the features and tonal qualit
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G.Manmadha, Rao, Raidu Babu D.N, Krishna Kanth P.S.L, B.Vinay, and V.Nikhil. "Reduction of Impulsive Noise from Speech and Audio Signals by using Sd-Rom Algorithm." International Journal of Recent Technology and Engineering (IJRTE) 10, no. 1 (2021): 265–68. https://doi.org/10.35940/ijrte.A5943.0510121.

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Removal of noise is the heart for speech and audio signal processing. Impulse noise is one of the most important noise which corrupts different parts in speech and audio signals. To remove this type of noise from speech and audio signals the technique proposed in this work is signal dependent rank order mean (SD-ROM) method in recursive version. This technique is used to replace the impulse noise samples based on the neighbouring samples. It detects the impulse noise samples based on the rank ordered differences with threshold values. This technique doesn’t change the features and tonal
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Zhu, You Lian, and Cheng Huang. "Median Morphological Filter Design Based on the PSO Algorithm." Applied Mechanics and Materials 128-129 (October 2011): 181–84. http://dx.doi.org/10.4028/www.scientific.net/amm.128-129.181.

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Design of morphological filter greatly depends on morphological operations and structuring elements selection. A filter design method used median closing morphological operation is proposed to enhance the image denoising ability and the PSO algorithm is introduced for structural elements selecting. The method takes the peak value signal-to-noise ratio (PSNR) as the cost function and may adaptively build unit structuring elements with zero square matrix. Experimental results show the proposed method can effectively remove impulse noise from a noisy image, especially from a low signal-to-noise r
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Dissertations / Theses on the topic "Peak signal noise ratio PSNR"

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Dandu, Sai Venkata Satya Siva Kumar, and Sujit Kadimisetti. "2D SPECTRAL SUBTRACTION FOR NOISE SUPPRESSION IN FINGERPRINT IMAGES." Thesis, Blekinge Tekniska Högskola, Institutionen för tillämpad signalbehandling, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-13848.

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Human fingerprints are rich in details called the minutiae, which can be used as identification marks for fingerprint verification. To get the details, the fingerprint capturing techniques are to be improved. Since when we the fingerprint is captured, the noise from outside adds to it. The goal of this thesis is to remove the noise present in the fingerprint image. To achieve a good quality fingerprint image, this noise has to be removed or suppressed and here it is done by using an algorithm or technique called ’Spectral Subtraction’, where the algorithm is based on subtraction of estimated n
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Mendes, Valenzuela Gracieth. "Mecanismo de seleção de rede em ambientes heterogêneos baseado em qualidade de experiência (qoe)." Universidade Federal de Pernambuco, 2011. https://repositorio.ufpe.br/handle/123456789/2728.

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Made available in DSpace on 2014-06-12T16:00:39Z (GMT). No. of bitstreams: 2 arquivo6834_1.pdf: 2552234 bytes, checksum: ff18190fd071f2e26f6470e29f084e5a (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2011<br>Conselho Nacional de Desenvolvimento Científico e Tecnológico<br>Com a crescente popularidade das redes sem fio e as tecnologias Wi-Fi (Wireless Fidelity), WiMAX (Worldwide Interoperability for Microwave Access), surgiu a necessidade de se promover uma convergência entre elas, visando oferecer ao usuário diversas oportunidades de con
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CRUZ, Hugo Alexandre Oliveira da. "Metodologia de predição de perda de propagação e qualidade de vídeo em redes sem fio indoor por meio de redes neurais artificiais." Universidade Federal do Pará, 2018. http://repositorio.ufpa.br/jspui/handle/2011/10029.

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Submitted by Kelren Mota (kelrenlima@ufpa.br) on 2018-06-14T18:39:25Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertacao_MetodologiaPredicaoPerda.pdf: 3699343 bytes, checksum: 3b43522af593666187f8aef07927421f (MD5)<br>Approved for entry into archive by Kelren Mota (kelrenlima@ufpa.br) on 2018-06-14T18:39:41Z (GMT) No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertacao_MetodologiaPredicaoPerda.pdf: 3699343 bytes, checksum: 3b43522af593666187f8aef07927421f (MD5)<br>Made available in DSpace
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Tsuda, Hirofumi. "Study on Communication System From the Perspective of Improving Signal-to-Noise Ratio." Kyoto University, 2019. http://hdl.handle.net/2433/242440.

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Belda, Ortega Román. "Mejora del streaming de vídeo en DASH con codificación de bitrate variable mediante el algoritmo Look Ahead y mecanismos de coordinación para la reproducción, y propuesta de nuevas métricas para la evaluación de la QoE." Doctoral thesis, Universitat Politècnica de València, 2021. http://hdl.handle.net/10251/169467.

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[ES] Esta tesis presenta diversas propuestas encaminadas a mejorar la transmisión de vídeo a través del estándar DASH (Dynamic Adaptive Streaming over HTTP). Este trabajo de investigación estudia el protocolo de transmisión DASH y sus características. A la vez, plantea la codificación con calidad constante y bitrate variable como modo de codificación del contenido de vídeo más indicado para la transmisión de contenido bajo demanda mediante el estándar DASH. Derivado de la propuesta de utilización del modo de codificación de calidad constante, cobra mayor importancia el papel que juegan los a
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Qian, Hua. "Power Efficiency Improvements for Wireless Transmissions." Diss., Georgia Institute of Technology, 2005. http://hdl.handle.net/1853/11649.

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Many communications signal formats are not power efficient because of their large peak-to-average power ratios (PARs). Moreover, in the presence of nonlinear devices such as power amplifiers (PAs) or mixers, the non-constant-modulus signals may generate both in-band distortion and out-of-band interference. Backing off the signal to the linear region of the device further reduces the system power efficiency. To improve the power efficiency of the communication system, one can pursue two approaches: i) linearize the PA; ii) reduce the high PAR of the input signal. In this dissertation, we fir
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Vergütz, Stéphany. "Uma combinação entre os critérios objetivo e subjetivo na classificação de imagens mamográficas comprimidas pelo método fractal." Universidade Federal de Uberlândia, 2013. https://repositorio.ufu.br/handle/123456789/14568.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior<br>Images are relevant sources of information in many areas of science and technology. The processing of such information improves and optimizes its use. The image compression causes the information representation is more efficient, reducing the amount of data required to represent an image. The objective of this study is to evaluate the performance of Fractal Compression technique onto mammograms through an association between the objective criteria, provided by Peak Signal Noise Ration (PSNR); and the subjective criteria, given by
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Šimoník, Petr. "Měřič odstupu signálu od šumu obrazových signálů." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2008. http://www.nusl.cz/ntk/nusl-217681.

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The diplomma thesis is dealing with possibilities of Signal to noise ratio measurement by method, which is based on direct measurement. It is chosen the most suitable method – signal and noise separation to two different parallel signal branches, where is measured signal strength in one branch and root mean square value in the other. The thesis is consisted of a concept of detail block scheme of Signal to noise ratio meter, which was designed in terms of theoretical knowledge. Particular functional blocks were circuit-designed, the active and passive parts were chosen and their function were d
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Ramkumar, M. "Some New Methods For Improved Fractal Image Compression." Thesis, 1996. https://etd.iisc.ac.in/handle/2005/1897.

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Ramkumar, M. "Some New Methods For Improved Fractal Image Compression." Thesis, 1996. http://etd.iisc.ernet.in/handle/2005/1897.

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Book chapters on the topic "Peak signal noise ratio PSNR"

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Ma, Xiaoyu, Kunmei Li, Zhiwei Wang, et al. "Hybrid Noise Eliminating Algorithm for Radar Target Images Based on the Time-Frequency Domain." In Lecture Notes in Civil Engineering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-4355-1_38.

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AbstractThe radar target imaging effect directly affects the resolution of the radar target, which affects the commander’s decision. However, the hybrid noise composed of speckle and Gaussian noise is one of the main affecting factors. The existing methods for image denoising are hard to eliminate the hybrid noise in radar images. Hence, this paper proposes a new hybrid noise elimination algorithm for the radar target image. Based on the strong correlation between wavelet coefficients, this algorithm first uses the wavelet coefficient correlation denoising algorithm (WCCDA) to filter the high-
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Zangana, Hewa Majeed, and Firas Mahmood Mustafa. "Wavelet-Autoencoder Hybrid Model for Enhanced Image Denoising in Medical Imaging." In Advances in Medical Diagnosis, Treatment, and Care. IGI Global, 2025. https://doi.org/10.4018/979-8-3693-9816-6.ch019.

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This chapter proposes a novel hybrid approach that combines the strengths of wavelet transform with the powerful learning capabilities of autoencoder networks to achieve superior denoising performance. By leveraging wavelet decomposition to process images at multiple scales and feeding these decomposed signals into a deep autoencoder network, we effectively suppress noise while maintaining high-frequency details. Extensive experiments demonstrate that our method outperforms existing techniques, yielding significant improvements in both peak signal-to-noise ratio (PSNR) and structural similarit
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Jiang, Ping. "A Study on Image Denoising Under Multi-Objective-Based Algorithm." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2024. http://dx.doi.org/10.3233/faia241120.

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In order to improve the image quality in neutron imaging, a denoising method combining particle swarm optimization (PSO) algorithm and wavelet threshold function is adopted in this study. The denoising threshold is adjusted by particle swarm optimization algorithm to effectively reduce Poisson noise and maintain image details. Experimental results show that compared with other methods, this method is more effective in removing noise, and can significantly improve the peak signal to noise ratio (PSNR) and reduce the mean square error (MSE) of the image, thus improving the image quality.
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Fradi, Marwa, Kais Bouallegue, Philippe Lasaygues, and Mohsen Machhout. "Automatic Noise Reduction in Ultrasonic Computed Tomography Image for Adult Bone Fracture Detection." In Biomedical Engineering. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.101714.

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Noise reduction in medical image analysis is still an interesting hot topic, especially in the field of ultrasonic images. Actually, a big concern has been given to automatically reducing noise in human-bone ultrasonic computed tomography (USCT) images. In this chapter, a new hardware prototype, called USCT, is used but images given by this device are noisy and difficult to interpret. Our approach aims to reinforce the peak signal-to-noise ratio (PSNR) in these images to perform an automatic segmentation for bone structures and pathology detection. First, we propose to improve USCT image quali
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Mercy, J. Sheela, and S. Silvia Priscila. "Efficient Noise Removal in Palmprint Images Using Various Filters in a Machine-Learning Approach." In Explainable AI Applications for Human Behavior Analysis. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-1355-8.ch011.

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A biological identification technique, palm print identification, takes advantage of the distinctive patterns on a person's palm for authentication. It falls under the broader category of biometrics, which deals with evaluating and statistically assessing each individual's distinctive personality characteristics. The efficiency of three well-known noise-removal methods the non-local mean (NLM) filter, Wiener filter, and median filter when utilized on palmprint images are examined in the present research. Peak signal-to-noise ratio (PSNR), mean squared error (MSE), and structural similarity ind
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Deshpande Anand and Patavardhan Prashant P. "Super-Resolution of Long Range Captured Iris Image Using Deep Convolutional Network." In Advances in Parallel Computing. IOS Press, 2017. https://doi.org/10.3233/978-1-61499-822-8-244.

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This chapter proposes a deep convolutional neural network based super-resolution framework to super-resolve and to recognize the long-range captured iris image sequences. The proposed framework is tested on CASIA V4 iris database by analyzing the peak signal-to-noise ratio (PSNR), structural similarity index matrix (SSIM) and visual information fidelity in pixel domain (VIFP) of the state-of-art algorithms. The performance of the proposed framework is analyzed for the upsampling factors 2 and 4 and achieved PSNRs of 37.42 dB and 34.74 dB respectively. Using this framework, we have achieved an
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Zangana, Hewa Majeed, and Firas Mahmood Mustafa. "A Novel Hybrid Wavelet-GAN Image Denoising System." In Advances in Computational Intelligence and Robotics. IGI Global, 2025. https://doi.org/10.4018/979-8-3693-9045-0.ch017.

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The hybrid approach offers two significant contributions; the first one by using wavelet trans-forms, the system achieves noise isolation and reduction across different frequency levels, ad-dressing both high- and low-frequency noise components effectively; and the second one the GAN framework introduces data-driven learning that enhances image details and restores subtle structures lost during the wavelet filtering process. Extensive experiments on various image datasets demonstrate that the proposed system outperforms conventional denoising techniques, such as traditional wavelet-based metho
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Hubert, G., and S. Silvia Priscila. "Efficient Noise Removal From Preterm Baby Retinopathy Images Using Various Filtering Approaches." In Clinical and Comparative Research on Maternal Health. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-5941-9.ch003.

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For healthcare practitioners to perform reliable and precise assessments, assuring early detection and appropriate treatment of retinal illnesses, high-quality, noise-free images, is essential. An essential step in improving the reliability and precision of medical diagnoses is the reduction of noise from premature newborns' retinopathy photos. Effective noise removal can be accomplished by using various filters and methods. In recent days, research has been on the effectiveness of noise removal methods is available, specifically the homomorphic filter (HF), laplacian of gaussian (LOG) filter
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Bhardwaj, Charu, Urvashi Sharma, Shruti Jain, and Meenakshi Sood. "Implementation and Performance Assessment of Biomedical Image Compression and Reconstruction Algorithms for Telemedicine Applications." In Research Anthology on Improving Medical Imaging Techniques for Analysis and Intervention. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-7544-7.ch080.

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Compression serves as a significant feature for efficient storage and transmission of medical, satellite, and natural images. Transmission speed is a key challenge in transmitting a large amount of data especially for magnetic resonance imaging and computed tomography scan images. Compressive sensing is an optimization-based option to acquire sparse signal using sub-Nyquist criteria exploiting only the signal of interest. This chapter explores compressive sensing for correct sensing, acquisition, and reconstruction of clinical images. In this chapter, distinctive overall performance metrics li
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Bhardwaj, Charu, Urvashi Sharma, Shruti Jain, and Meenakshi Sood. "Implementation and Performance Assessment of Biomedical Image Compression and Reconstruction Algorithms for Telemedicine Applications." In Medical Data Security for Bioengineers. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7952-6.ch003.

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Compression serves as a significant feature for efficient storage and transmission of medical, satellite, and natural images. Transmission speed is a key challenge in transmitting a large amount of data especially for magnetic resonance imaging and computed tomography scan images. Compressive sensing is an optimization-based option to acquire sparse signal using sub-Nyquist criteria exploiting only the signal of interest. This chapter explores compressive sensing for correct sensing, acquisition, and reconstruction of clinical images. In this chapter, distinctive overall performance metrics li
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Conference papers on the topic "Peak signal noise ratio PSNR"

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Saravanan, M. S., Faiyaz Ahmad, and R. T. Thivya Lakshmi. "Compression technique by Analyzing Peak Signal to Noise Ratio value using various Machine Learning Algorithms." In 2024 Asian Conference on Intelligent Technologies (ACOIT). IEEE, 2024. https://doi.org/10.1109/acoit62457.2024.10939329.

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Kong, Qiuqiang, Yong Xu, Philip J. B. Jackson, Wenwu Wang, and Mark D. Plumbley. "Single-Channel Signal Separation and Deconvolution with Generative Adversarial Networks." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/381.

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Single-channel signal separation and deconvolution aims to separate and deconvolve individual sources from a single-channel mixture. Single-channel signal separation and deconvolution is a challenging problem in which no prior knowledge of the mixing filters is available. Both individual sources and mixing filters need to be estimated. In addition, a mixture may contain non-stationary noise which is unseen in the training set. We propose a synthesizing-decomposition (S-D) approach to solve the single-channel separation and deconvolution problem. In synthesizing, a generative model for sources
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M, Jeba Jenitha, Kani Jesintha D, and Mahalakshmi P. "Noise Adaptive Fuzzy Switching Median Filters for Removing Gaussian Noise." In The International Conference on scientific innovations in Science, Technology, and Management. International Journal of Advanced Trends in Engineering and Management, 2023. http://dx.doi.org/10.59544/ozsc7243/ngcesi23p113.

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Recently, in all image processing systems, image restoration plays a major role and it forms the major part of image processing systems. Medical images such as brain Magnetic Resonance Imaging (MRI), ultrasound images of liver and kidney, retinal images and images of uterus images are often affected by various types of noises such as Gaussian noise and salt and pepper noise. All image restoration techniques attempts to remove various types of noises. This paper deals with various filters namely Mean Filter, Averaging Filter, Median Filter, Adaptive Median Filter, Adaptive Weighted Median Filte
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Kaur, Jinder, Gurwinder Kaur, and Ashwani Kumar. "An Improved Method to Remove Salt and Pepper Noise in Noisy Images." In International Conference on Women Researchers in Electronics and Computing. AIJR Publisher, 2021. http://dx.doi.org/10.21467/proceedings.114.23.

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In the field of image processing, removal of noise from Gray scale as well as RGB images is an ambitious task. The important function of noise removal algorithm is to eliminate noise from a noisy image. The salt and pepper noise (SPN) is frequently arising into Gray scale and RGB images while capturing, acquiring and transmitting over the insecure several communication mechanisms. In past, the numerous noise removal methods have been introduced to extract the noise from images adulterated with SPN. The proposed work introduces the SPN removal algorithm for Gray scale at low along with high den
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Negreiros, Ana Cláudia Souza Vidal de, Gilson Giraldi, Heron Werner, and Ítalo Messias Feliz Santos. "Self-Supervised Image Denoising Methods: an Application in Fetal MRI." In Workshop de Visão Computacional. Sociedade Brasileira de Computação - SBC, 2023. http://dx.doi.org/10.5753/wvc.2023.27546.

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The process of image denoising in magnetic resonance imaging (MRI) is more and more common and important in the medical area. However, it is usual that state-of-the-art deep learning methods require pair images (clean and noisy ones) to train the models which poses limitations in practice. In this sense, this work applied two recent techniques that do not need a clean image to train the models and reached good results for denoising tasks. We applied the NOISE2NOISE (N2N) and the NOISE2VOID (N2V) learning approaches and compared the results for denoising tasks using a fetal MRI dataset. The res
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S. Mahdi, Noor, and Ghadah K. AL-Khafaji. "Adaptive Color Image Compression Using ADJPEG and ISUQ of Hierarchical Decomposition Scheme." In 5TH INTERNATIONAL CONFERENCE ON COMMUNICATION ENGINEERING AND COMPUTER SCIENCE (CIC-COCOS'24). Cihan University-Erbil, 2024. http://dx.doi.org/10.24086/cocos2024/paper.1544.

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This paper introduced a lossy color compression system of transform coding (TC) based of discrete wavelet transform (DWT), discrete cosine transform (DCT) and quantization schemes to achieve high compression ratio (CR) with preserving quality. The proposed compression system comprises the following steps, firstly, separating the image into source/non source color bands, then quantizing the source band uniformity, followed by decomposing an image by a three-level DWT and applying huffman coding to the approximation sub band, and compressed the details sub bands of each level by iterative scalar
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7

Subramanian, Nandhini, ,. Jayakanth Kunhoth, Somaya Al-Maadeed, and Ahmed Bouridane. "Stego-eHealth: An eHealth System for Secured Transfer of Medical Images using Image Steganography." In Qatar University Annual Research Forum & Exhibition. Qatar University Press, 2021. http://dx.doi.org/10.29117/quarfe.2021.0155.

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COVID pandemic has necessitated the need for virtual and online health care systems to avoid contacts. The transfer of sensitive medical information including the chest and lung X-ray happens through untrusted channels making it prone to many possible attacks. This paper aims to secure the medical data of the patients using image steganography when transferring through untrusted channels. A deep learning method with three parts is proposed – preprocessing module, embedding network and the extraction network. Features from the cover image and the secret image are extracted by the preprocessing
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8

Sena, Antonio Wilker O. de, Gleison de O. Medeiros, and João Victor C. Carmona. "Análise Comparativa de Modelos de Propagação e Qualidade de Experiência em Redes 5G: Implicações para o Planejamento de Redes Urbanas." In Encontro Unificado de Computação do Piauí. Sociedade Brasileira de Computação, 2025. https://doi.org/10.5753/enucompi.2025.9564.

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Este trabalho investiga a eficiência de diferentes modelos de propagação em redes móveis de quinta geração (5G), com foco na análise do impacto desses modelos na qualidade da experiência do usuário (QoE). Três modelos de propagação foram analisados: Log Distance, Three Log Distance e Cost 231, utilizando simulações em ambiente virtual com o simulador NS-3. As métricas de QoE utilizadas foram o Mean Opinion Score (MOS) e o Peak Signal-to-Noise Ratio (PSNR). Os resultados indicaram que o modelo Cost 231 demonstrou o melhor desempenho em cenários ultra-densos, mantendo a qualidade da comunicação
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Silveira Júnior, Garibaldi da, Gilberto Kreisler, Bruno Zatt, Daniel Palomino, and Guilherme Correa. "Multi-Domain Spatio-Temporal Deformable Fusion model for video quality enhancement." In Proceedings of the Brazilian Symposium on Multimedia and the Web. Sociedade Brasileira de Computação - SBC, 2024. http://dx.doi.org/10.5753/webmedia.2024.241618.

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Lossy video compression introduces artifacts that can degrade the perceived visual quality of the video. Improving the quality of compressed videos involves mitigating these artifacts through filtering techniques. Deep neural network (DNN) models have emerged as powerful tools for this task, demonstrating effectiveness in artifact reduction. However, traditional approaches typically evaluate these models using videos compressed by a single coding standard, limiting their applicability across diverse codecs. To address this limitation, this study proposes a novel multi-domain architecture built
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Najeeb, Al Anood, Somaya Al Maadeed, and Noor Al Maadeed. "Performance Analysis of DCT and WDCT Algorithms in Image Steganography." In Qatar University Annual Research Forum & Exhibition. Qatar University Press, 2021. http://dx.doi.org/10.29117/quarfe.2021.0167.

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Frequency domain techniques such as Discrete Cosine Transform (DCT) and Warped Discrete Cosine Transform (WDCT) ensures high accuracy when compared with the spatial domain techniques. Therefore, these image steganographic methods were evaluated using public datasets to compare the performance of DCT and WDCT. After performing different tests using the datasets in each of the algorithms, a comparative analysis is made in terms of the Peak Signal-to-Noise Ratio (PSNR) metrics. The results indicate that the stego image generated after embedding the secret acquires high imperceptibility and robust
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