Semi-blind deconvolution of defocused image with MCMA
In this paper, a new approach for blurred noisy image restoration is presented. The blurred noisy image is assumed to be the output of a linear space-invariant system with an unknown point spread function contaminated by an additive noise. The scheme passes the blurred noisy image through a two-dimensional finite impulse response filter whose parameters are updated by the modified constant modulus algorithm with averaging and variable step size. When convergence occurs, the output of the filter is an estimate of the unobserved true image. Experimental results show that the proposed scheme is effective.
Su Liyun Liu Ruihua Li Fenglan Li Jiaojun
School of Mathematics and Statistics Chongqing University of Technology Chongqing, China Library Chongqing University of Technology Chongqing, China School of Electronic Information Chongqing University of Technology Chongqing, China
国际会议
太原
英文
45-49
2010-10-22（万方平台首次上网日期，不代表论文的发表时间）