A nonconvex l1(l1−l2) model for image restoration with impulse noise

2020 ◽  
Vol 378 ◽  
pp. 112934
Author(s):  
Jingjing Liu ◽  
Anqi Ni ◽  
Guoxi Ni
Keyword(s):  
Image Restoration ◽  
Impulse Noise

Nonconvex-TV Based Image Restoration with Impulse Noise Removal

2017 ◽  
Vol 10 (3) ◽  
pp. 1627-1667 ◽  
Author(s):  
Xiongjun Zhang ◽  
Minru Bai ◽  
Michael K. Ng
Keyword(s):  
Image Restoration ◽  
Impulse Noise ◽  
Noise Removal ◽  
Impulse Noise Removal

AN ADAPTIVE DIFFUSION SCHEME FOR IMAGE RESTORATION AND SELECTIVE SMOOTHING

2012 ◽  
Vol 12 (01) ◽  
pp. 1250003 ◽  
Author(s):  
V. B. SURYA PRASATH ◽  
ARINDAMA SINGH
Keyword(s):  
Image Restoration ◽  
Impulse Noise ◽  
Scale Space ◽  
Edge Information ◽  
Spatial Function ◽  
Diffusion Scheme ◽  
Gradient Based ◽  
Local Edge ◽  
Well Posed ◽  
Selective Smoothing

Anisotropic partial differential equation (PDE)-based image restoration schemes employ a local edge indicator function typically based on gradients. In this paper, an alternative pixel-wise adaptive diffusion scheme is proposed. It uses a spatial function giving better edge information to the diffusion process. It avoids the over-locality problem of gradient-based schemes and preserves discontinuities coherently. The scheme satisfies scale space axioms for a multiscale diffusion scheme; and it uses a well-posed regularized total variation (TV) scheme along with Perona-Malik type functions. Median-based weight function is used to handle the impulse noise case. Numerical results show promise of such an adaptive approach on real noisy images.

Adaptive Two-Pass Median Filter Based on Support Vector Machines for Image Restoration

2004 ◽  
Vol 16 (2) ◽  
pp. 333-354 ◽  
Author(s):  
Tzu-Chao Lin ◽  
Pao-Ta Yu
Keyword(s):  
Support Vector Machines ◽  
Image Restoration ◽  
Impulse Noise ◽  
Median Filter ◽  
Support Vector ◽  
New Approach ◽  
Median Filters ◽  
Vector Machines ◽  
Impulse Detector

In this letter, a novel adaptive filter, the adaptive two-pass median (ATM) filter based on support vector machines (SVMs), is proposed to preserve more image details while effectively suppressing impulse noise for image restoration. The proposed filter is composed of a noise decision maker and two-pass median filters. Our new approach basically uses an SVM impulse detector to judge whether the input pixel is noise. If a pixel is detected as a corrupted pixel, the noise-free reduction median filter will be triggered to replace it. Otherwise, it remains unchanged. Then, to improve the quality of the restored image, a decision impulse filter is put to work in the second-pass filtering procedure. As for the noise suppressing both fixed-valued and random-valued impulses without degrading the quality of the fine details, the results of our extensive experiments demonstrate that the proposed filter outperforms earlier median-based filters in the literature. Our new filter also provides excellent robustness at various percentages of impulse noise.

Advance in Image and Audio Restoration and their Assessments: A Review

2021 ◽  
Vol 12 (2) ◽  
pp. 1-16
Author(s):  
Omar H. Mohammed ◽  
Basil Sh. Mahmood
Keyword(s):  
Image Restoration ◽  
Gaussian Noise ◽  
Impulse Noise ◽  
Degradation Process ◽  
Motion Blur ◽  
Original Image ◽  
Restoration Techniques ◽  
Degradation Models ◽  
Noise Impulse ◽  
Audio Restoration

Image restoration is the process of restoring the original image from a degraded one. Images can be affected by various types of noise, such as Gaussian noise, impulse noise, and affected by blurring, which is happened during image recordings like motion blur, Out-of-Focus Blur, and others. Image restoration techniques are used to reverse the effect of noise and blurring. Restoration of distorted images can be done using some information about noise and the blurring nature or without any knowledge about the image degradation process. Researchers have proposed many algorithms in this regard; in this paper, different noise and degradation models and restoration methods will be discussed and review some researches in this field.

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