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arXiv · 2610.25195

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

Reza Parvaz
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Abstract

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.

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Reza Parvaz. 2026-10-18. Image Restoration with Impulse Noise Based on Minimax Concave Penalty: Grayscale and Color Images. https://arxiv.org/abs/2610.25195

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