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An MMSE approach to nonlocal image denoising: Theory and practical implementation

An MMSE approach to nonlocal image denoising: Theory and practical implementation
학술지명 Journal Of Visual Communication And Image Representation ISSN 1047-3203
SCI 유무 SCI(E) 게재연월 2012-04 Vol. 23 No. 3
표준화된 순위정보영향력지수 67.96 IF 1.122 Citation 2

An MMSE approach to nonlocal image denoising: Theory and practical implementation
저자 Chul Lee, ChulWoo Lee, ChangSu Kim
초록
A nonlocal minimum mean square error (MMSE) image denoising algorithm is proposed in this work. Based on the Bayesian estimation theory, we first derive that the conventional nonlocal means filter is an MMSE estimator in the special case of noise-free nonlocal neighbors. Then, we develop the nonlocal MMSE denoising filter that can minimize the mean square error (MSE) of a denoised block in more general cases of noisy nonlocal neighbors. Furthermore, the proposed algorithm searches nonlocal neighbors from an external database as well as the entire input image to improve the performance even when a noisy block may not have similar blocks within the image. Since the extended search range demands a higher computational burden, we develop a probabilistic tree-based search method to reduce the computational complexity. Simulation results show that the proposed algorithm provides significantly better denoising performance than the conventional nonlocal means filter.
keyword Image denoising, Nonlocal means filter, Minimum mean square error (MMSE), denoising, Bayesian estimation, Noisy nonlocal neighbors, Probabilistic tree search, External database, Image restoration

An MMSE approach to nonlocal image denoising: Theory and practical implementation
과제명 3D SLAM 기반 삼차원 환경 실시간 모델링 기술 개발
연구기관 고려대학교 연구책임자 도낙주