Markov random field modeling in median pyramidal transform domain for denoising applications

Ilya Gluhovsky; Vladimir P. Melnik; Ilya Shmulevich

doi:10.1117/12.424984

8 May 2001 Markov random field modeling in median pyramidal transform domain for denoising applications

Ilya Gluhovsky, Vladimir P. Melnik, Ilya Shmulevich

Proceedings Volume 4304, Nonlinear Image Processing and Pattern Analysis XII; (2001) https://doi.org/10.1117/12.424984
Event: Photonics West 2001 - Electronic Imaging, 2001, San Jose, CA, United States

Abstract

We consider a median pyramidal transform for denoising applications. Traditional techniques of pyramidal denoising are similar to those in wavelet-based methods. In order to remove noise, they use the thresholding of transform coefficients. We propose to model the structure of the transform coefficients as a Markov random field. The goal of modeling transform coefficients is to retain significant coefficients on each scale and to discard the rest. Estimation of the transform coefficient structure is obtained via a Markov chain sampler. The advantage of our method is that we are able to utilize the interactions between transform coefficients, both within each scale and among the scales, which leads to denoising improvement as demonstrated by numerical simulations.

Citation Download Citation

Ilya Gluhovsky, Vladimir P. Melnik, and Ilya Shmulevich "Markov random field modeling in median pyramidal transform domain for denoising applications", Proc. SPIE 4304, Nonlinear Image Processing and Pattern Analysis XII, (8 May 2001); https://doi.org/10.1117/12.424984

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KEYWORDS

Denoising

Magnetorheological finishing

Adaptive optics

Digital filtering

Reconstruction algorithms

Nonlinear filtering

Electronic filtering

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