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Dual Splitting Method For Sparsity Signal Restoration With Impulsive Noise
2017
Journal of Information Hiding and Multimedia Signal Processing
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We consider sparsity signal restoration with impulsive noise by sparsity regularization. It is challenging due to the fact that both fidelity and regularization term lack of differentiability. ...
We propose a novel dual splitting method and show that one can overcome the non-differentiability and instability by adding a smooth splitting 2 regularization term to the original optimization functional ...
This paper is supported by Project supported by the National Nature Science Foundation of China (no.41304093), the Fundamental Research Funds for the Central Universities (no.2572015CB19), Heilongjiang ...
dblp:journals/jihmsp/DingX17
fatcat:lsphnajnkrc4vay2khetl63s34
A Primal-Dual Proximal Algorithm for Sparse Template-Based Adaptive Filtering: Application to Seismic Multiple Removal
2014
IEEE Transactions on Signal Processing
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The approach demonstrates significantly good performance in low signal-to-noise ratio conditions, both for simulated and real field seismic data. ...
Unveiling meaningful geophysical information from seismic data requires to deal with both random and structured "noises". ...
For real signals, we propose to infer those constants from other methods. In practice, alternative cruder filtering or restoration algorithms indeed exist, with the same purpose. ...
doi:10.1109/tsp.2014.2331614
fatcat:hyvgktsolncb5k3m7gus74viz4
Jump-Sparse and Sparse Recovery Using Potts Functionals
2014
IEEE Transactions on Signal Processing
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We highlight the capability of the method by comparing it with classical and recent approaches such as TV minimization (jump-sparse signals), orthogonal matching pursuit, iterative hard thresholding, and ...
We then propose a new optimization method for these functionals which is based on dynamic programming and the alternating direction method of multipliers (ADMM). ...
The iPotts-ADMM recovers the true signal almost perfectly; in particular, the correct number of jumps. For impulsive noise, the iPotts-ADMM and the TV method perform equally well. ...
doi:10.1109/tsp.2014.2329263
fatcat:uncc7tdwzbeipdsmdvdvqwue7e
A constrained-based optimization approach for seismic data recovery problems
2014
2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Not only classical constraints, such as sparsity, are considered here, but also constraints expressed through hyperplanes, onto which the projection is easy to compute. ...
Random and structured noise both affect seismic data, hiding the reflections of interest (primaries) that carry meaningful geophysical interpretation. ...
With weak primary/multiple decorrelation, poor data stationarity or higher noise levels, traditional methods fail. ...
doi:10.1109/icassp.2014.6854025
dblp:conf/icassp/PhamCDP14
fatcat:iajyc62lbrdwtp4kmbmo4d55eq
Efficient Sparse Recovery and Demixing Using Nonconvex Regularization
2019
IEEE Access
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For sparsity promotion in sparse demixing, the convex 1 norm is of the most popular but it has a bias problem. ...
INDEX TERMS Alternative direction method of multipliers, inpainting, nonconvex optimization, sparse demixing, sparse recovery, signal separation. ...
of impulsive noise. ...
doi:10.1109/access.2019.2915311
fatcat:v5nrrc5qqzafxodwbtwleulhnq
A constrained-based optimization approach for seismic data recovery problems
[article]
2014
arXiv
pre-print
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Not only classical constraints, such as sparsity, are considered here, but also constraints expressed through hyperplanes, onto which the projection is easy to compute. ...
Random and structured noise both affect seismic data, hiding the reflections of interest (primaries) that carry meaningful geophysical interpretation. ...
With weak primary/multiple decorrelation, poor data stationarity or higher noise levels, traditional methods fail. ...
arXiv:1406.4687v1
fatcat:gmsnhbdsx5h2tna2qudk5dlkca
ECG Signal Denoising and Reconstruction Based on Basis Pursuit
2021
Applied Sciences
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The electrocardiogram (ECG) is widely used for the diagnosis of heart diseases. However, ECG signals are easily contaminated by different noises. ...
This method introduces dual variables, adds a secondary penalty term, and reduces constraint conditions through alternate optimization to optimize the original variable and the dual variable at the same ...
Its main idea is to reconstruct and restore the signal with less sampled data [9] [10] [11] [12] . Appl. Sci. 2021, 11 CS subverts the traditional signal sampling method. ...
doi:10.3390/app11041591
fatcat:ydzhswfu4bbcthlfdzututjq6y
Salt and pepper noise removal method based on stationary Framelet transform with non-convex sparsity regularization
[article]
2023
arXiv
pre-print
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For example, the noise location information is often ignored and the sparsity of the salt and pepper noise is often described by L1 norm, which cannot illustrate the sparse variables clearly. ...
Finally, experiments are conducted to verify the proposed method and compare it with some current state-of-the-art denoising methods. ...
For instance, Wang adopted the p l quasi-norm to depict the sparsity of impulse noise and proposed a denoising method based on low-order overlapping group sparsity with p l quasi-norm and achieved promising ...
arXiv:2110.09113v9
fatcat:stwb3ypas5bq3ejvfglfqhgvte
Total Variation with Overlapping Group Sparsity for Image Deblurring under Impulse Noise
2015
PLoS ONE
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In this paper, in order to alleviate the staircase effect, we propose a new model for restoring blurred images with impulse noise. ...
Compared with other methods, numerical results illustrate that the proposed method, can significantly improve the restoration quality, both in avoiding staircase effects and in terms of peak signal-to-noise ...
Tao for providing us the code ADM2CTVL1 (CTY) in [26] . Also, they would like to thank the referees and the academic editor for their careful reviews and helpful comments.
Author Contributions ...
doi:10.1371/journal.pone.0122562
pmid:25874860
pmcid:PMC4398568
fatcat:f42ektk4jnehrbctq442tm3lwm
Semi-automatic tumor contouring method using PET and MRI medical images
[chapter]
2015
Computational Vision and Medical Image Processing V
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Sonmez
v
A nonsmooth nonconvex sparsity-promoting variational approach for deblurring images
corrupted by impulse noise
87
A. Lanza, S. Morigi & F. ...
PhellanPrimal-dual method for continuous max-flow approaches 17K Wei, X.-C. Tai, T.F. Chan & S. Leung A. A. Putilov, O. G. Donskaya & E. G. ...
doi:10.1201/b19241-35
fatcat:e2e3xkry4bdypfle7ll7cjuhim
Nonconvex Wavelet Thresholding Total Variation Denoising Method for Planetary Gearbox Fault Diagnosis
2020
IEEE Access
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Comparisons with the soft thresholding and basis pursuit denoising (BPD) methods show that the proposed method can accurately estimate the fault features from vibration signals, which means that the proposed ...
In this paper, a nonconvex wavelet thresholding total variation (WATV) denoising method is proposed for planetary gearbox fault diagnosis, which combines wavelet-domain sparsity and total variation (TV ...
; x (t) ∈ R N is the fault signal, which contains impulsive components with periodic characteristics caused by localized gearbox faults; and w (t) ∈ R N is white Gaussian noise. ...
doi:10.1109/access.2020.2988467
fatcat:nklxollq3fbunbvmstjcgzkc5a
Relaxing Tight Frame Condition in Parallel Proximal Methods for Signal Restoration
2012
IEEE Transactions on Signal Processing
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2011 pre-print arXiv:1105.5275v3 fatcat:k47zkva6ebbb7fj3gmcwm3ugzyOther Versions
In our simulations, it is applied to the deconvolution of data corrupted with Poisson noise or Laplacian noise by using (non-tight) discrete dual-tree wavelet representations and filter bank structures ...
restoration problems. ...
Introduction Many works in signal/image processing are concerned with data restoration problems. ...
doi:10.1109/tsp.2011.2173684
fatcat:qvavgi6mmvawvhxdw4mv6nllde
Hybrid regularization image deblurring in the presence of impulsive noise
2013
Journal of Visual Communication and Image Representation
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In this paper, we propose a new approach for restoring images corrupted by blur and impulse noise. ...
The experiments on a set of image deblurring benchmark problems show that the proposed method outperforms previous state-of-the-art methods for image restoration. ...
Acknowledgments The authors are very grateful to the Editor and the two referees for their helpful comments and suggestions on the original version of the paper, which led to the improved version of the ...
doi:10.1016/j.jvcir.2013.09.006
fatcat:uvqxfyag6vffbiz2gjk4v3ybya
Dual Autoencoder Network with Separable Convolutional Layers for Denoising and Deblurring Images
2022
Journal of Imaging
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The research includes Gaussian noise (Gaussian blur), Poisson noise, speckle noise, and random impulse noise. ...
A dual autoencoder employing separable convolutional layers for image denoising and deblurring is represented. ...
Impulse Noise Salt and pepper noise is another name for impulse noise where sharp and rapid disruptions in the visual signal might create this noise. ...
doi:10.3390/jimaging8090250
pmid:36135415
pmcid:PMC9502178
fatcat:tl2zpqnxezduhdazxi5kbhynou
RNLp: Mixing Nonlocal and TV-Lp Methods to Remove Impulse Noise from Images
2018
Journal of Mathematical Imaging and Vision
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The denoising performance of the proposed methods is on par with state of the art approaches, and the remarkable fact is that, unlike other successful variational approaches for impulse noise removal, ...
Keywords Image denoising · impulse noise · variational methods · patch-based methods · convex optimization J. Delon, C. Sutour MAP5, Université Paris Descartes. ...
For a low noise level, all methods efficiently remove noise. ...
doi:10.1007/s10851-018-0856-3
fatcat:cjgh4bhp5jc4lghijxl7yf72zm
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