A Perception-Based Error Criterion and the Design of Stack Filters for Image Restoration

Restoration of images with translation invariant filters always involves a tradeoff between detail preservation and noise removal. The tradeoff which is best is that which produces an image that a human being would judge to be closest to the original image. In this paper, we show how such an optimal tradeoff can be achieved by combining a filter design algorithm with a nonlinear model of the human visual system.

[1]  Petros Maragos,et al.  Morphological filters-Part I: Their set-theoretic analysis and relations to linear shift-invariant filters , 1987, IEEE Trans. Acoust. Speech Signal Process..

[2]  Thomas S. Huang,et al.  Image processing , 1971 .

[3]  Edward J. Coyle,et al.  A fast algorithm for designing stack filters , 1999, IEEE Trans. Image Process..

[4]  Edward J. Coyle,et al.  Minimum mean absolute error estimation over the class of generalized stack filters , 1990, IEEE Trans. Acoust. Speech Signal Process..

[5]  Yeong-Taeg Kim,et al.  Fast algorithms for training stack filters , 1994, IEEE Trans. Signal Process..

[6]  O. Yli-Harja.  Formula for the joint distribution of stack filters , 1994, IEEE Signal Processing Letters.

[7]  Moncef Gabbouj,et al.  A training framework for stack and Boolean filtering-fast optimal design procedures and robustness case study , 1996, IEEE Trans. Image Process..

[8]  Edward J. Coyle,et al.  Stack filters , 1986, IEEE Trans. Acoust. Speech Signal Process..

[9]  J. Fitch,et al.  Median filtering by threshold decomposition , 1984 .

[10]  Edward J. Coyle,et al.  Threshold decomposition of multidimensional ranked order operations , 1985 .

[11]  Andrew B. Watson,et al.  Digital images and human vision , 1993 .

[12]  Petros Maragos,et al.  Morphological filters-Part II: Their relations to median, order-statistic, and stack filters , 1987, IEEE Trans. Acoust. Speech Signal Process..

[13]  Jaakko Astola,et al.  Analysis of the properties of median and weighted median filters using threshold logic and stack filter representation , 1991, IEEE Trans. Signal Process..