Hybrid inter- and intra-wavelet scale image restoration

被引:35
作者
Zhang, L
Bao, P [1 ]
Wu, XL
机构
[1] Hong Kong Polytech Univ, Dept Comp, Kowloon, Hong Kong, Peoples R China
[2] Chinese Univ Hong Kong, Dept Informat Engn, Shatin, Hong Kong, Peoples R China
[3] Univ Western Ontario, Dept Comp Sci, London, ON, Canada
关键词
image restoration; overcomplete wavelet expansion; inter- and intra-scale dependency; LMMSE;
D O I
10.1016/S0031-3203(02)00350-3
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper exploits both the inter- and intra-scale interdependencies that exist in wavelet coefficients to improve image restoration from noise-corrupted data. Using an over-complete wavelet expansion, we group the wavelet coefficients with the same spatial orientation at several scales. We then apply the linear minimum mean squared-error estimation to smooth noise. This scheme exploits the inter-scale correlation information of wavelet coefficients. To exploit the intra-scale dependencies, we calculate the co-variance matrix of each vector locally using a centered square-shaped window. Experiments show that the proposed hybrid scheme significantly outperforms methods exploiting only the intra-. or inter-scale dependencies. The performance of noise removal also depends on wavelet filters. In our experiments a biorthogonal wavelet, which best characterizes the image inter-scale dependencies, achieves the best results. (C) 2003 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:1737 / 1746
页数:10
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