Image Denoising Using Multiresolution Singular Value Decomposition Transform

Malini, S.; Moni, R. S.

doi:10.1016/j.procs.2015.02.114

Cited by 19 publications

(7 citation statements)

References 13 publications

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“…To obtain a similar performance to the multi-scale analysis of WT, MRSVD has been applied to detect abrupt changes in waveforms, and to further locate the boundaries of transition segments. MRSVD has better performance than WT, especially in a strong noise environment, and does not require the choice of a mother wavelet as in WT [20][21][22].…”

Section: The Multi-resolution Singular Value Decomposition Methodsmentioning

confidence: 99%

An Adaptive Approach for Voltage Sag Automatic Segmentation

Xiao

Zhang

et al. 2018

Energies

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Voltage sag characterization is essential for extracting information about a sag event’s origin and how sag events impact sensitive equipment. In response to such needs, more characteristics are required, such as the phase-angle jump, point-on-wave, unbalance, and sag type. However, the absence of an effective automatic segmentation method is a barrier to obtaining these characteristics. In this paper, an automatic segmentation method is proposed to improve this situation. Firstly, an extended voltage sag characterization method is described, in which segmentation plays an important role. Then, a multi-resolution singular value decomposition method is introduced to detect the boundaries of each segment. Further, the unsolved problem of how to set a threshold adaptively for different waveforms is addressed, in which the sag depth, the mean square error, and the entropy of the sag waveform are considered. Simulation data and field measurements are utilized to validate the effectiveness and reliability of the proposed method. The results show that the accuracies of both boundary detection and segmentation obtained using the proposed method are higher than those obtained using existing methods. In general, the proposed method can be implemented into a power quality monitoring system as a preprocess to support related research activities.

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Section: The Multi-resolution Singular Value Decomposition Methodsmentioning

confidence: 99%

An Adaptive Approach for Voltage Sag Automatic Segmentation

Xiao

Zhang

et al. 2018

Energies

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“…The watermarking system's robustness is calculated using Normalized correlation (NC) [32,33] and, between the original watermark W and the extracted watermark W+, which is defined in terms of Eq. (8).…”

Section: Performance Measuresmentioning

confidence: 99%

Secure Watermarking Scheme for Color DICOM Images in Telemedicine Applications

Singh¹,

Abu-Hamatta²,

Kumar³

et al. 2022

Computers, Materials &Amp; Continua

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Teleradiology plays a vital role in the medical field, which permits transmitting medical and imaging data over a communication network. It ensures data reliability and provides convenient communication for clinical interpretation and diagnostic purposes. The transmission of this medical data over a network raises the problems of legal, ethical issues, privacy, and copyright authenticity. The copyright protection of medical images is a significant issue in the medical field. Watermarking schemes are used to address these issues. A gray-level or binary image is used as a watermark frequently in color image watermarking schemes. In this paper, the authors propose a novel non-blind medical image watermarking scheme based on 2-D Lifting Wavelet Transform (LWT), Multiresolution Singular Value Decomposition (MSVD), and LU factorization to improve the robustness and authenticity of medical images. In this scheme, multiple color watermarks are embedded into the colored DICOM (Digital Imaging and Communications in Medicine) images obtained from Color Doppler images (DICOM format), and the average results achieved by our proposed scheme is 46.84 db for Peak Signal-to-Noise Ratio (PSNR), 37.46 db for Signal-to-Noise Ratio (SNR), 0.99 for Quality of Image and 0.998 for Normalized Correlation for various image processing attacks. These results make our watermarking technique an ideal candidate for medical image watermarking.

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“…The SVD is also a widely recognized technique that has been used for image denoising [22][23][24]. Rajwade et al [25] successfully used the higher order singular value decomposition (HOSVD) for filtering natural images, although this technique require complex criteria, which involve solving optimization models, to establish the low rank approximation for filtering noise.…”

Section: Introductionmentioning

confidence: 99%

Non-Local SVD Denoising of MRI Based on Sparse Representations

Leal

Zurek

Leal³

2020

Sensors

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Magnetic Resonance (MR) Imaging is a diagnostic technique that produces noisy images, which must be filtered before processing to prevent diagnostic errors. However, filtering the noise while keeping fine details is a difficult task. This paper presents a method, based on sparse representations and singular value decomposition (SVD), for non-locally denoising MR images. The proposed method prevents blurring, artifacts, and residual noise. Our method is composed of three stages. The first stage divides the image into sub-volumes, to obtain its sparse representation, by using the KSVD algorithm. Then, the global influence of the dictionary atoms is computed to upgrade the dictionary and obtain a better reconstruction of the sub-volumes. In the second stage, based on the sparse representation, the noise-free sub-volume is estimated using a non-local approach and SVD. The noise-free voxel is reconstructed by aggregating the overlapped voxels according to the rarity of the sub-volumes it belongs, which is computed from the global influence of the atoms. The third stage repeats the process using a different sub-volume size for producing a new filtered image, which is averaged with the previously filtered images. The results provided show that our method outperforms several state-of-the-art methods in both simulated and real data.

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Image Denoising Using Multiresolution Singular Value Decomposition Transform

Cited by 19 publications

References 13 publications

An Adaptive Approach for Voltage Sag Automatic Segmentation

An Adaptive Approach for Voltage Sag Automatic Segmentation

Secure Watermarking Scheme for Color DICOM Images in Telemedicine Applications

Non-Local SVD Denoising of MRI Based on Sparse Representations

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