Relevant bibliographies by topics / Redundant Wavelet Transform (RWT)

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Academic literature on the topic 'Redundant Wavelet Transform (RWT)'

Author: Grafiati
Published: 3 June 2025
Last updated: 22 June 2025

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Journal articles on the topic "Redundant Wavelet Transform (RWT)"

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Novamizanti, Ledya, Irma Safitri, Hafizhan Bhamakerti Arindaka, and Iwan Iwut Tritoasmoro. "Watermarking berbasis Redundant Discrete Wavelet Transform dan Arnold Transform pada Citra Medis." Jurnal Teknik Elektro 13, no. 2 (2021): 48–55. http://dx.doi.org/10.15294/jte.v13i2.31691.

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In telemedicine, data transmission in digital medical images and electronic medical records through the internet is vulnerable to various threats of theft and manipulation. Image watermarking is needed to provide authentication and security to medical images. This paper proposes an image watermarking scheme based on Redundant Discrete Wavelet Transform (RDWT) and Discrete Cosine Transform (DCT) with watermark encryption using Arnold transform. First, the original host medical image was decomposed into four subbands using RDWT. Then, DCT is applied to the LH subband of the RDWT. On the other hand, the watermark is scrambled using Arnold transform to ensure identity security. The singular value of the watermarked image is obtained by modifying the singular value of the host image and the watermark. Tests were carried out on different medical images, namely X-ray, MRI, CT, and ultrasound, with a watermark in a proprietary logo. The host medical image is the same size as the watermark image. The result of this study can provide high authentication, imperceptibility and security in medical images, with an average PSNR value of 65.67 dB, SSIM 1, BER 0, NC 1. This scheme is resistant to JPEG compression, noise addition, filtering, image sharpening, image enhancement, geometric operations, motion blur, image sharpening, and histogram equalization.
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Roa’a M. Al_airaji, Ibtisam A. Aljazaery, and Haider TH Salim ALRikabi. "Adaptive HDR Image Blind Watermarking Approach Based on Redundant Discrete Wavelet Transform." International Journal of Interactive Mobile Technologies (iJIM) 17, no. 10 (2023): 136–54. http://dx.doi.org/10.3991/ijim.v17i10.38795.

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Remarkable success has been recorded in the usage of digital watermarking which is aimed at protecting the intellectual property of multimedia content. In this paper, a new tone mapping attack-resistant high dynamic range (HDR) image zero-watermarking algorithm is proposed. In this algorithm extraction of stable and invariant features are extracted for efficient zero-watermarking through the application of the redundant discrete wavelet transform (RDWT) to the HDR image. The first step involves transforming the HDR image to HVS color space, and RDWT is implemented using the V-channel so that the LL sub-band which contains the strong structure contents of the image is obtained. The second step involves dividing the LL sub-band into non-overlapping blocks, which are afterwards subjected to the process of transformation through the use of the singular value decomposition (SVD) so that the U matrix can be extracted. Third, the use of an Auto-Regressive (AR) prediction technique was employed in generating a local relationship model and comparison is done to facilitate the production of a binary feature mask. In the fourth process, hybrid chaotic mapping (HCM) is used to generate blended watermark so that the security of the watermark can be fortified. Lastly, the computation of an effective zero-watermark is achieved through the implementation of an exclusive-or operation on the blended watermark and the binary feature mask. Based on the results, the approach presented in this study demonstrated superior performance in terms of withstanding TM attacks and other attacks associated with image processing.
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Al-Dossary, Saleh. "Preconditioning seismic data for channel detection." Interpretation 3, no. 1 (2015): T1—T4. http://dx.doi.org/10.1190/int-2014-0031.1.

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Random seismic noise, present in all 3D seismic data sets, hampers manual interpretation by geoscientists and automatic analysis by a computer program. As a result, many noise-suppression techniques have been developed to enhance image quality. Accurately suppressing seismic noise without damaging image details is crucial in preserving small-scale geologic features for channel detection. The automatic detection of channel patterns theoretically should be easy because of their unique spatial signatures and scales, which differentiate them from other common 3D geobodies. For example, one notable channel characteristic has high local linearity: Spatial coherency is much greater in one direction than in other directions. A variety of techniques, such as spatial filters, can be used to enhance this “slender” channel feature in areas of high signal-to-noise ratio (S/N). Unfortunately, these spatial filters may also reduce the edge detectability in areas of low S/N. In this paper, I compared the effectiveness of three noise reduction filters: (1) running average, (2) redundant wavelet transform (RWT), and (3) polynomial fitting. I demonstrated the usefulness of these filters prior to edge detection to enhance channel patterns in seismic data collected from Saudi Arabia. The data examples demonstrated that RWT and polynomial fitting can successfully preserve, enhance, and delineate channel edges that were not visible in conventional seismic amplitude displays, whereas the running average filter further smeared the detectability of channel edges.
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Zhu, Xuan, Xu Feng Zhang, Qiu Ju Li, Ji Yao Tao, and Ben Yuan Li. "A Novel Image Inpainting Method Based on Sparse Decomposition." Applied Mechanics and Materials 738-739 (March 2015): 573–77. http://dx.doi.org/10.4028/www.scientific.net/amm.738-739.573.

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Redundant Discrete Wavelet Transform (RDWT) and Wavelet Atomic Transform (WAT) are proposed in this paper as a couple of dictionaries to get the structure and texture basing on morphological component decomposition. Then, basing on the fact that the structure and texture have different characteristics, in this paper we use curvature driven diffusion model and Criminisi texture synthesis method to inpaint the structure and texture respectively. At last, compound the inpainted structure and texture and get the inpainting result. The experiment results show the new method can not only decompose the image very well, but also inpaint the image with strong and fairing edge, complete and clear texture .This method shows better results in image inpainting compared to the classical ones.
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Gao, Lin, Tiegang Gao, Jie Zhao, and Yonglei Liu. "Reversible Watermarking in Digital Image Using PVO and RDWT." International Journal of Digital Crime and Forensics 10, no. 2 (2018): 40–55. http://dx.doi.org/10.4018/ijdcf.2018040103.

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This article proposed a reversible digital image watermarking scheme using PVO and Redundant Discrete Wavelet Transform (RDWT). The PVO was introduce to the proposed scheme to enhance the embedding capacity. By embedding the watermark in the RDWT coefficients, the proposed scheme exploited the visual masking property of RDWT to achieve better visual quality. Also, the proposed scheme has better performance on embedding capacity because the RDWT has several sub-band coefficients for embedding. The experimental results on natural and medical images suggests that the proposed scheme could meet the demand of perceptional quality with better embedding capacity than former schemes.
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Gao, Lin, Yunjie Zhang, and Guoyan Li. "Reversible Watermarking in Medical Images Using Sub-Sample and Multiple Histogram Modification." Journal of Information Technology Research 13, no. 4 (2020): 75–90. http://dx.doi.org/10.4018/jitr.2020100106.

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This paper proposed a reversible medical image watermarking scheme using multiple histogram modification (MHM) and redundant discrete wavelet transform (RDWT). The MHM was introduced to the proposed scheme to enhance the embedding capacity. By embedding the watermark in the RDWT coefficients, the proposed scheme exploited the visual masking property of RDWT to guarantee the visual quality. Also, the proposed scheme has better performance on embedding capacity because the RDWT has several sub-band coefficients for embedding. The experimental results on medical images suggests that the proposed scheme could meet the demand of perceptional quality with better embedding capacity than former schemes.
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Ren, Dianwei, and Mohamed G. Abdelsalam. "Tracing along-strike structural continuity in the Neoproterozoic Allaqi-Heiani Suture, southern Egypt using principal component analysis (PCA), fast Fourier transform (FFT), and redundant wavelet transform (RWT) of ASTER data." Journal of African Earth Sciences 44, no. 2 (2006): 181–95. http://dx.doi.org/10.1016/j.jafrearsci.2005.10.010.

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Singh, Siddharth, and Tanveer J. Siddiqui. "Robust Image Data Hiding Technique for Copyright Protection." International Journal of Information Security and Privacy 7, no. 2 (2013): 44–56. http://dx.doi.org/10.4018/jisp.2013040103.

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A robust image data-hiding scheme for copyright protection is proposed and simulated. The scheme uses a combination of redundant discrete wavelet transform (RDWT), singular value decomposition (SVD) and spread spectrum technique. The embedding is done by spreading the copyright mark into the singular values of middle frequency sub-bands of RDWT coefficients of the cover image. Chaotic sequence is used for spreading. The use of chaotic sequence and RDWT increases security and robustness of the proposed scheme. Simulation results show that the proposed scheme achieves higher security and robustness against filtering, addition of noise, JPEG compression, sharpening, gamma correction, resizing, rotation, and histogram equalization than other existing techniques for copyright protection.
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Gao, Lin, Tiegang Gao, and Jie Zhao. "Reversible Watermarking in Medical Image Using RDWT and Sub-Sample." International Journal of Digital Crime and Forensics 7, no. 4 (2015): 1–18. http://dx.doi.org/10.4018/ijdcf.2015100101.

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This paper proposed a reversible medical image watermarking scheme using Redundant Discrete Wavelet Transform (RDWT) and sub-sample. To meet the highly demand of the perceptional quality, the proposed scheme embedding the watermark by modifying the RDWT coefficients. The sub-sample scheme is introduced to the proposed scheme for the enhancement of the embedding capacity. Moreover, to meet the need of security, a PWLCM based image encryption algorithm is introduced for encrypting the image after the watermark embedding. The experimental results suggests that the proposed scheme not only meet the highly demand of the perceptional quality, but also have better embedding capacity than former DWT based scheme. Also the encryption scheme could protect the image contents efficiently.
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Subramaniam, Jalab, Ibrahim, and Mohd Noor. "Improved Image Splicing Forgery Detection by Combination of Conformable Focus Measures and Focus Measure Operators Applied on Obtained Redundant Discrete Wavelet Transform Coefficients." Symmetry 11, no. 11 (2019): 1392. http://dx.doi.org/10.3390/sym11111392.

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The image is the best information carrier in the current digital era and the easiest to manipulate. Image manipulation causes the integrity of this information carrier to be ambiguous. The image splicing technique is commonly used to manipulate images by fusing different regions in one image. Over the last decade, it has been confirmed that various structures in science and engineering can be demonstrated more precisely by fractional calculus using integrals or derivative operators. Many fractional-order-based techniques have been used in the image-processing field. Recently, a new specific fractional calculus, called conformable calculus, was delivered. Herein, we employ the combination of conformable focus measures (CFMs), and focus measure operators (FMOs) in obtaining redundant discrete wavelet transform (RDWT) coefficients for improving the image splicing forgery detection. The process of image splicing disorders the content of tampered image and causes abnormality in the image features. The spliced region’s boundaries are usually blurring to avoid detection. To make use of the blurred information, both CFMs and FMOs are used to calculate the degree of blurring of the tampered region’s boundaries for image splicing detection. The two public image datasets IFS-TC and CASIA TIDE V2 are used for evaluation of the proposed method. The obtained results of the proposed method achieved accuracy rate 98.30% for Cb channel on IFS-TC image dataset and 98.60% of the Cb channel on CASIA TIDE V2 with 24-D feature vector. The proposed method exhibited superior results compared with other image splicing detection methods.
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Dissertations / Theses on the topic "Redundant Wavelet Transform (RWT)"

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Herrmann, Felix J., and Gilles Hennenfent. "Non-linear data continuation with redundant frames." Canadian Society of Exploration Geophysicists, 2005. http://hdl.handle.net/2429/518.

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We propose an efficient iterative data interpolation method using continuity along reflectors in seismic images via curvelet and discrete cosine transforms. The curvelet transform is a new multiscale transform that provides sparse representations for images that comprise smooth objects separated by piece-wise smooth discontinuities (e.g. seismic images). The advantage of using curvelets is that these frames are sparse for high-frequency caustic-free solutions of the wave-equation. Since we are dealing with less than ideal data (e.g. bandwidth-limited), we compliment the curvelet frames with the discrete cosine transform. The latter is motivated by the successful data continuation with the discrete Fourier transform. By choosing generic basis functions we circumvent the necessity to make parametric assumptions (e.g. through linear/parabolic Radon or demigration) regarding the shape of events in seismic data. Synthetic and real data examples demonstrate that our algorithm provides interpolated traces that accurately reproduce the wavelet shape as well as the AVO behavior along events in shot gathers.
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Handl, Marek. "Vlnková filtrace signálů EKG." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2013. http://www.nusl.cz/ntk/nusl-220046.

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The work deals with the wavelet transformation, focusing on wavelet transforms with discrete time (DTWT). The practical part is focused on the implementation of redundant packet DTWT and its use in the filtration of ECG signals. The main part of the work is to design wiener filter that uses redundant packet DTWT, designed to eliminate interference myopotentials of ECG signals. The actual solution is implemented in Matlab. Testing is performed on the library CSE using noise model myopotentials used to noising original signals. For optimum parameters designed filter is used the genetic algorithm (GA). The work is carried out comparing the proposed filter redundant packet DTWT a variant of redundant dyadic DTWT.
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Books on the topic "Redundant Wavelet Transform (RWT)"

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Redundant Discrete Wavelet Transform Based Super-Resolution Using Sub- Pixel Image Registration. Storming Media, 2003.

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Book chapters on the topic "Redundant Wavelet Transform (RWT)"

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Wang, Guitang, Wenjuan Liu, Ruihuang Wang, Xiaowu Huang, and Feng Wang. "Unsupervised Texture Segmentation Based on Redundant Wavelet Transform." In Advanced Technology in Teaching - Proceedings of the 2009 3rd International Conference on Teaching and Computational Science (WTCS 2009). Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-11276-8_59.

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Singh, Rajiv, and Ashish Khare. "Redundant Discrete Wavelet Transform Based Medical Image Fusion." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04960-1_44.

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Tronicke, Jens, and Erika Lück. "Multi-scale analysis and interpretation of multi-method geophysical data sets." In Advances in On- and Offshore Archaeological Prospection. Universitätsverlag Kiel | Kiel University Publishing, 2023. http://dx.doi.org/10.38072/978-3-928794-83-1/p90.

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Redundant wavelet transform is proposed to analyze multi-method databases. Multi-scale analyses are used to separate target features from noise and background. As a main result, we generate composite images optimized for complementary information.
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Suliman, Ahmed, and Robert Li. "Video Compression Using Variable Block Size Motion Compensation with Selective Subpixel Accuracy in Redundant Wavelet Transform." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32467-8_88.

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Thanki, Rohit M., Surekha Borra, and Komal R. Borisagar. "A Hybrid Watermarking Technique for Copyright Protection of Medical Signals in Teleradiology." In Research Anthology on Telemedicine Efficacy, Adoption, and Impact on Healthcare Delivery. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-8052-3.ch034.

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Today, an individual's health is being monitored for diagnosis and treatment of diseases upon analyzing various medical data such as images and signals. Modifications of this medical data when it is transferred over an open communication channel or network leads to deviations in diagnosis and creates a serious health issue for any individual. Digital watermarking techniques are one of the solutions for providing protection to multimedia contents. This chapter gives requirements and various techniques for the security of medical data using watermarking. This chapter also demonstrates a novel hybrid watermarking technique based on fast discrete curvelet transform (FDCuT), redundant discrete wavelet transform (RDWT), and discrete cosine transform (DCT). This watermarking technique can be used for securing medical various types of medical images and ECG signals over an open communication channel.
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Thanki, Rohit M., Surekha Borra, and Komal R. Borisagar. "A Hybrid Watermarking Technique for Copyright Protection of Medical Signals in Teleradiology." In Handbook of Research on Information Security in Biomedical Signal Processing. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-5152-2.ch017.

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Today, an individual's health is being monitored for diagnosis and treatment of diseases upon analyzing various medical data such as images and signals. Modifications of this medical data when it is transferred over an open communication channel or network leads to deviations in diagnosis and creates a serious health issue for any individual. Digital watermarking techniques are one of the solutions for providing protection to multimedia contents. This chapter gives requirements and various techniques for the security of medical data using watermarking. This chapter also demonstrates a novel hybrid watermarking technique based on fast discrete curvelet transform (FDCuT), redundant discrete wavelet transform (RDWT), and discrete cosine transform (DCT). This watermarking technique can be used for securing medical various types of medical images and ECG signals over an open communication channel.
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Gao, Lin, Tiegang Gao, and Jie Zhao. "Reversible Watermarking in Medical Image Using RDWT and Sub-Sample." In Cryptography. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1763-5.ch029.

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This paper proposed a reversible medical image watermarking scheme using Redundant Discrete Wavelet Transform (RDWT) and sub-sample. To meet the highly demand of the perceptional quality, the proposed scheme embedding the watermark by modifying the RDWT coefficients. The sub-sample scheme is introduced to the proposed scheme for the enhancement of the embedding capacity. Moreover, to meet the need of security, a PWLCM based image encryption algorithm is introduced for encrypting the image after the watermark embedding. The experimental results suggests that the proposed scheme not only meet the highly demand of the perceptional quality, but also have better embedding capacity than former DWT based scheme. Also the encryption scheme could protect the image contents efficiently.
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Conference papers on the topic "Redundant Wavelet Transform (RWT)"

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Cui, Suxia, Yonghui Wang, and Cajetan M. Akujuobi. "Redundant Wavelet Transform in Biomedical Image Application." In ASME 2006 Frontiers in Biomedical Devices Conference. ASMEDC, 2006. http://dx.doi.org/10.1115/nanobio2006-18043.

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The change of blood vessel is very important in the biomedical research, because creatures, including human beings tempt to adjust themselves to fit for the new environments. For example, if a tumor was found inside a human body and diagnosed as cancer, to get rid of this tumor is important, but to prevent the tumor to reach out to other organs is more crucial. The goal of starving the tumor can be achieved by preventing new blood vessels to grow into it. Another example is the wound healing which can be enhanced by encouraging blood vessels to reach the damaged parts. Both applications focus on the trace of the growing blood vessels. There are several trials on how to trace blood vessels, we can category them into three main approaches: window-based methods, classifier-based methods and tracking-based methods [1]. In this paper, the authors explore the usage of RDWT in this specific area of biomedical image application. Redundant wavelet transform (RDWT) has the property that all of the RDWT coefficients locate at the same spatial location as in the original spatial image, which makes it preferable for feature extraction and signal analysis [2]. With the already successful applications of RDWT in image processing and video coding [3,4], the authors built a new system to segment blood vessels using RDWT coefficient mask.
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Huang, Lin, Liping Ji, Ping Hu, and Tiejun Yang. "Pedestrian detection based on redundant wavelet transform." In SPIE/COS Photonics Asia, edited by Qionghai Dai and Tsutomu Shimura. SPIE, 2016. http://dx.doi.org/10.1117/12.2246044.

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Wang, Yonghui, and Suxia Cui. "Using redundant wavelet transform in video watermarking." In Optics East 2005, edited by Anthony Vetro, Chang Wen Chen, C. C. J. Kuo, Tong Zhang, Qi Tian, and John R. Smith. SPIE, 2005. http://dx.doi.org/10.1117/12.634296.

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Wang, Yonghui, Suxia Cui, Jian-ao Lian, and Cajetan M. Akujuobi. "Image object removal in redundant wavelet transform domain." In IS&T/SPIE Electronic Imaging, edited by Jaakko T. Astola, Karen O. Egiazarian, Nasser M. Nasrabadi, and Syed A. Rizvi. SPIE, 2009. http://dx.doi.org/10.1117/12.805912.

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Li, Deqiang, Shaowei Guo, and Zelin Shi. "Redundant Lifted Fast Wavelet Transform for Signal Compression." In 2006 8th international Conference on Signal Processing. IEEE, 2006. http://dx.doi.org/10.1109/icosp.2006.344491.

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Gajbhar, Shrishail S., and Manjunath V. Joshi. "Image denoising using redundant finer directional wavelet transform." In 2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG). IEEE, 2013. http://dx.doi.org/10.1109/ncvpripg.2013.6776251.

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Tao Gao and Zheng-guang Liu. "Moving video object segmentation based on redundant wavelet transform." In 2008 International Conference on Information and Automation (ICIA). IEEE, 2008. http://dx.doi.org/10.1109/icinfa.2008.4607987.

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Singh, Richa, Mayank Vatsa, and Afzel Noore. "Multimodal Medical Image Fusion Using Redundant Discrete Wavelet Transform." In 2009 Seventh International Conference on Advances in Pattern Recognition (ICAPR). IEEE, 2009. http://dx.doi.org/10.1109/icapr.2009.97.

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Tronicke, Jens, Philipp Koyan, and Niklas Allroggen. "The redundant wavelet transform to process and interpret GPR data." In 18th International Conference on Ground Penetrating Radar, Golden, Colorado, 14–19 June 2020. Society of Exploration Geophysicists, 2020. http://dx.doi.org/10.1190/gpr2020-104.1.

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WEN, XEU-BING, XUE-ZHANG LIANG, YI-NAN HAN, and JING-NA JI. "Mammographic image enhancement and denoising based on redundant wavelet transform." In Proceedings of the International Computer Conference 2006. World Scientific Publishing Company, 2006. http://dx.doi.org/10.1142/9789812772763_0132.

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