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Image Restoration with Impulse Noise Based on Minimax Concave Penalty: Grayscale and Color Images
Reza Parvaz

Image Restoration with Impulse Noise Based on Minimax Concave Penalty: Grayscale and Color Images

Author / Organization:
Published 2026 Verification Pending

Overview & Synopsis

In today's world-where social networks play a significant role-images serve as one of the most important tools for transferring concepts. Image degradation caused by noise or blurring hinders the effective transmission of the information we expect to derive from an image. Consequently, developing image restoration methods capable of revealing crucial information is of great importance. In this work, a model for impulse noise image restoring is proposed by using a Minimax Concave Penalty. The proposed model is applicable to both color and grayscale images. Then, a numerical algorithm based on the alternating direction method of multipliers is introduced, and the convergence of the method is analyzed both theoretically and numerically. In the final step, the proposed method is evaluated through simulations on several examples, and the results demonstrate its effectiveness.

Indexed from repository: arXiv (arxiv.org)
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Document Information

Document Title Image Restoration with Impulse Noise Based on Minimax Concave Penalty: Grayscale and Color Images
Author / Organization Reza Parvaz
Subject & Discipline eess.IV
Publication Year 2026
License / Rights arXiv Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website arXiv (arxiv.org)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-275755
Original Source Link Visit Source Page on arxiv.org »