tailieunhanh - Báo cáo hóa học: " Research Article Iterative Estimation Algorithms Using Conjugate Function Lower Bound and Minorization-Maximization with Applications in Image Denoising"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Iterative Estimation Algorithms Using Conjugate Function Lower Bound and Minorization-Maximization with Applications in Image Denoising | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2008 Article ID 429128 12 pages doi 2008 429128 Research Article Iterative Estimation Algorithms Using Conjugate Function Lower Bound and Minorization-Maximization with Applications in Image Denoising Guang Deng1 and Wai-Yin Ng2 1 Department of Electronic Engineering La Trobe University Bundoora Victoria 3086 Australia 2 Department of Information Engineering The Chinese University of Hong Kong Shatin Hong Kong Correspondence should be addressed to Guang Deng Received 19 September 2007 Revised 3 January 2008 Accepted 11 February 2008 Recommended by Hubert Cardot A fundamental problem in signal processing is to estimate signal from noisy observations. This is usually formulated as an optimization problem. Optimizations based on variational lower bound and minorization-maximization have been widely used in machine learning research signal processing and statistics. In this paper we study iterative algorithms based on the conjugate function lower bound CFLB and minorization-maximization MM for a class of objective functions. We propose a generalized version of these two algorithms and show that they are equivalent when the objective function is convex and differentiable. We then develop a CFLB MM algorithm for solving the MAP estimation problems under a linear Gaussian observation model. We modify this algorithm for wavelet-domain image denoising. Experimental results show that using a single wavelet representation the performance of the proposed algorithms makes better than that of the bishrinkage algorithm which is arguably one of the best in recent publications. Using complex wavelet representations the performance of the proposed algorithm is very competitive with that of the state-of-the-art algorithms. Copyright 2008 G. Deng and . Ng. This is an open access article distributed under the Creative Commons Attribution License which permits .