A well-balanced reaction-diffusion model for texture image denoising

Jia-Qiang Gong; Xiao-Ning Li

doi:10.1117/12.2014024

13 March 2013 A well-balanced reaction-diffusion model for texture image denoising

Jia-Qiang Gong, Xiao-Ning Li

Proceedings Volume 8783, Fifth International Conference on Machine Vision (ICMV 2012): Computer Vision, Image Analysis and Processing; 878316 (2013) https://doi.org/10.1117/12.2014024
Event: Fifth International Conference on Machine Vision (ICMV 12), 2012, Wuhan, China

Abstract

Important information, such as textures or edge, is often lost or blurred in the process of traditional denoising. In this paper we present a well balanced reaction-diffusion equation combined new harmonic analysis to resolve this problem better. A mixed diffusivity term is used to control the diffusion process to smooth and maintain essential image characteristics. While in reaction terms we employ wave atoms and curvelets shrinkage to preserve and enhance textures and edges. Experiment results and comparisons show the good performance of the proposed model for texture and edge preserving in the process of denoising especially as the noise increase.

Citation Download Citation

Jia-Qiang Gong and Xiao-Ning Li "A well-balanced reaction-diffusion model for texture image denoising", Proc. SPIE 8783, Fifth International Conference on Machine Vision (ICMV 2012): Computer Vision, Image Analysis and Processing, 878316 (13 March 2013); https://doi.org/10.1117/12.2014024

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KEYWORDS

Denoising

Diffusion

Chemical species

Signal to noise ratio

Image processing

Image denoising

Plutonium

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