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Collection of inverse problems in image processing via Alternating Direction Method (ADM), Alternating Minimization Method (AMA), Group Sparse signal denoising and Majorization-Minimization optimization based image/signal processing

MATLAB 100.00%

image-signal-processing's Introduction

This folder contains implementations and re-implementations of some image restoration algorithms using mainly the popular Alternating Direction Methods of Multipliers (ADMM).

Some of the codes included are:

  1. Split Bregman Total Variation Denoising/Deblurring of Image
  2. ALM/ADMM Total Variation Denoising/Deblurring of Image
  3. Non-convex Lp-norm (0 < p <1) Total Variation Deblurring using ADMM/ALM and IRL1 (Iterative Reweighted L1).
  4. Second Order ALM/ADMM Total Variation Denoising/Deblurring (TV image restoration using the 2nd Order Derivative operator).
  5. Robust Principal Componant Analysis (RPCA) for sparse noise restoration (impulse noise). Solved using ADMM.
  6. Low rank matrix completion (LRMC) using ADMM. Example code is applied for missing pixel image restoration (Inpainting).
  7. The state-of-the-art L0-TV by Yuan and Ghanem for impulse noise restoration (using pure ADMM).

If you find any mistakes or bugs, Please DO NOT HESITATE to contact me ! at [email protected].

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