Patch-based Contour Prior Image Denoising for Salt and Pepper Noise

2018/08/26 by Bo Fu, Fu, Bo, Xiaoyang Zhao +5
Computer Science · Engineering · #Advanced Image Fusion Techniques #Advanced Image Processing Techniques #FOS: Computer and information sciences #Image and Signal Denoising Methods #Multimedia (cs.MM)

paper · pdf · doi:10.48550/arxiv.1808.08567

openalex publication_date 2018/08/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

The salt and pepper noise brings a significant challenge to image denoising technology, i.e. how to removal the noise clearly and retain the details effectively? In this paper, we propose a patch-based contour prior denoising approach for salt and pepper noise. First, noisy image is cut into patches as basic representation unit, a discrete total variation model is designed to extract contour structures; Second, a weighted Euclidean distance is designed to search the most similar patches, then, corresponding contour stencils are extracted from these similar patches; At the last, we build filter from contour stencils in the framework of regression. Numerical results illustrate that the proposed method is competitive with the state-of-the-art methods in terms of the peak signal-to-noise (PSNR) and visual effects.

Citations

• Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries

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