A Minorization-Maximization Algorithm for Maximum a Posteriori Signal Estimation

Author

Deng, Guang ; Ng, Wai-Yin

Author_Institution

Dept. of Electron. Eng., La Trobe Univ., Bundoora, Vic.

Volume

2

fYear

2006

fDate

14-19 May 2006

Abstract

We develop an iterative algorithm based on minorization-maximization optimization to determine the maximum a posteriori estimate of the signal. We focus on linear Gaussian signal model with a family of heavy-tailed prior distributions which can be represented as scale mixture of Gaussian. We then modify the proposed algorithm for wavelet domain image denoising. Experimental results show that using complex wavelet representations, the performance of the proposed algorithm is very competitive with that of the state-of-the-art algorithms

Keywords

Gaussian processes; image denoising; image representation; maximum likelihood estimation; minimax techniques; wavelet transforms; complex wavelet representations; heavy-tailed prior distributions; iterative algorithm; linear Gaussian signal model; maximum a posteriori signal estimation; minorization-maximization optimization algorithm; wavelet domain image denoising; Cost function; Distribution functions; Estimation; Image denoising; Iterative algorithms; Signal processing; Signal processing algorithms; Vectors; Wavelet coefficients; Wavelet domain;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on

Conference_Location

Toulouse

ISSN

1520-6149

Print_ISBN

1-4244-0469-X

Type

conf

DOI

10.1109/ICASSP.2006.1660418

Filename

1660418