Wavelet domain blind image separation

Mahieddine M. Ichir; Ali Mohammad-Djafari

doi:10.1117/12.508134

13 November 2003 Wavelet domain blind image separation

Mahieddine M. Ichir, Ali Mohammad-Djafari

Proceedings Volume 5207, Wavelets: Applications in Signal and Image Processing X; (2003) https://doi.org/10.1117/12.508134
Event: Optical Science and Technology, SPIE's 48th Annual Meeting, 2003, San Diego, California, United States

Abstract

In this work, we consider the problem of blind source separation in the wavelet domain via a Bayesian estimation framework. We use the sparsity and multiresolution properties of the wavelet coefficients to model their distribution by heavy tailed prior probability laws: the generalized exponential family and the Gaussian mixture family. Appropriate MCMC algorithms are developed in each case for the estimation purposes and simulation results are presented for comparaison.

Citation Download Citation

Mahieddine M. Ichir and Ali Mohammad-Djafari "Wavelet domain blind image separation", Proc. SPIE 5207, Wavelets: Applications in Signal and Image Processing X, (13 November 2003); https://doi.org/10.1117/12.508134

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