MMSE nonlocal means denoising algorithm for Poisson noise removal

Author

Lee, Chul ; Lee, Chulwoo ; Kim, Chang-Su

Author_Institution

Sch. of Electr. Eng., Korea Univ., Seoul, South Korea

fYear

2011

fDate

11-14 Sept. 2011

Firstpage

2561

Lastpage

2564

Abstract

A nonlocal minimum mean square error (MMSE) image denoising algorithm to remove Poisson noise is proposed in this work. Based on the Bayesian estimation theory, we first derive the nonlocal MMSE denoising filter, which can minimize the mean square error (MSE) of a denoised block. Then, we develop an approximation of the filter for practical implementation. Simulation results show that the proposed algorithm provides significantly better denoising performance than the conventional nonlocal means filter and its recent extension for Poisson noise.

Keywords

Bayes methods; Poisson distribution; filtering theory; image denoising; mean square error methods; Bayesian estimation theory; MMSE denoising filter; MMSE nonlocal means denoising algorithm; Poisson noise removal; image denoising algorithm; minimum mean square error; Approximation algorithms; Approximation methods; Image processing; Noise; Noise measurement; Noise reduction; Vectors; Bayesian estimation; Image denoising; MMSE denoising; Poisson noise; nonlocal means (NLM) filter;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing (ICIP), 2011 18th IEEE International Conference on

Conference_Location

Brussels

ISSN

1522-4880

Print_ISBN

978-1-4577-1304-0

Electronic_ISBN

1522-4880

Type

conf

DOI

10.1109/ICIP.2011.6116186

Filename

6116186