Image restoration using Gaussian scale mixtures in overcomplete oriented pyramids

Javier Portilla

doi:10.1117/12.615847

17 September 2005 Image restoration using Gaussian scale mixtures in overcomplete oriented pyramids

Javier Portilla

Proceedings Volume 5914, Wavelets XI; 59141F (2005) https://doi.org/10.1117/12.615847
Event: Optics and Photonics 2005, 2005, San Diego, California, United States

Abstract

Gaussian Scale Mixtures (GSMs) in overcomplete oriented pyramids are, arguably, one of the most powerful available tools for image denoising: 1) they provide a new mathematical frame for modelling the variance-adaptation problem, an approach used in image denoising for the last 25 years; 2) they are applicable to contaminating sources of any spectral density; 3) they yield the smallest L2-norm distortion results in simulations under white Gaussian noise, up to this date; and 4) they allow for a solution, for the first time, to the problem of denoising images affected by unknown covariance noise. In this work, we focus first on the general properties of the GSMs. Then, we review the different ways GSMs have been used in overcomplete oriented pyramids (MAP-z-GSM, BLS-GSM, spatially variant GSM), and their applications: classical denoising, signal-dependent noise removal, unknown covariance noise removal and deblurring.

Citation Download Citation

Javier Portilla "Image restoration using Gaussian scale mixtures in overcomplete oriented pyramids", Proc. SPIE 5914, Wavelets XI, 59141F (17 September 2005); https://doi.org/10.1117/12.615847

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