Fundamentals of digital image processing
Fundamentals of digital image processing
Oscillating Patterns in Image Processing and Nonlinear Evolution Equations: The Fifteenth Dean Jacqueline B. Lewis Memorial Lectures
Wavelet Algorithms for High-Resolution Image Reconstruction
SIAM Journal on Scientific Computing
A Variational Approach to Remove Outliers and Impulse Noise
Journal of Mathematical Imaging and Vision
Efficient Minimization Methods of Mixed l2-l1 and l1-l1 Norms for Image Restoration
SIAM Journal on Scientific Computing
Image Deblurring in the Presence of Impulsive Noise
International Journal of Computer Vision
Deconvolution: a wavelet frame approach
Numerische Mathematik
Restoration of Chopped and Nodded Images by Framelets
SIAM Journal on Scientific Computing
Iterative Algorithms Based on Decoupling of Deblurring and Denoising for Image Restoration
SIAM Journal on Scientific Computing
An Efficient TVL1 Algorithm for Deblurring Multichannel Images Corrupted by Impulsive Noise
SIAM Journal on Scientific Computing
A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
SIAM Journal on Imaging Sciences
A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
SIAM Journal on Imaging Sciences
A Fast Algorithm for Edge-Preserving Variational Multichannel Image Restoration
SIAM Journal on Imaging Sciences
A New Alternating Minimization Algorithm for Total Variation Image Reconstruction
SIAM Journal on Imaging Sciences
Fast Two-Phase Image Deblurring Under Impulse Noise
Journal of Mathematical Imaging and Vision
An Efficient Primal-Dual Method for $L^1$TV Image Restoration
SIAM Journal on Imaging Sciences
Image deblurring in the presence of salt-and-pepper noise
Scale-Space'05 Proceedings of the 5th international conference on Scale Space and PDE Methods in Computer Vision
An augmented Lagrangian approach to general dictionary learning for image denoising
Journal of Visual Communication and Image Representation
Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization
IEEE Transactions on Image Processing
Deblurring of Color Images Corrupted by Impulsive Noise
IEEE Transactions on Image Processing
Framelet Algorithms for De-Blurring Images Corrupted by Impulse Plus Gaussian Noise
IEEE Transactions on Image Processing
An Efficient Algorithm for l0 Minimization in Wavelet Frame Based Image Restoration
Journal of Scientific Computing
Non-convex hybrid total variation for image denoising
Journal of Visual Communication and Image Representation
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Image deblurring is one of the fundamental problems in the image processing and computer vision fields. In this paper, we propose a new approach for restoring images corrupted by blur and impulse noise. The existing methods used to address this problem are based on minimizing the objective functional, which is the sum of the L"1-data fidelity term, and the total variation (TV) regularization term. However, TV introduces staircase effects. Thus, we propose a new objective functional that combines the tight framelet and TV to restore images corrupted by blur and impulsive noise while mitigating staircase effects. The minimization of the new objective functional presents a computational challenge. We propose a fast minimization algorithm by employing the augmented Lagrangian technique. 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.