Title :
Deblurring two-tone images by a joint estimation approach using higher-order statistics
Author :
Li, Ta-Hsin ; Lii, Ke-Shin
Author_Institution :
Dept. of Stat., Texas A&M Univ., College Station, TX, USA
Abstract :
A method is proposed for the restoration of linearly blurred two-tone images without requiring the knowledge of the blur parameters. The method jointly estimates the original image and the blur parameters based on some statistical parameters at the output of an inverse filter. Unlike some other blind image restoration procedures, the proposed method does not require the estimation or modeling of the statistical properties of the original image, yet can be justified even for non-i.i.d. images
Keywords :
filtering theory; higher order statistics; image restoration; image segmentation; minimisation; parameter estimation; blur parameters; deblurring two-tone images; higher-order statistics; image restoration; inverse filter; joint estimation approach; statistical parameters; Blind equalizers; Character recognition; Deconvolution; Eyes; Higher order statistics; Humans; Image recognition; Image restoration; Nonlinear filters; Pixel;
Conference_Titel :
Higher-Order Statistics, 1997., Proceedings of the IEEE Signal Processing Workshop on
Conference_Location :
Banff, Alta.
Print_ISBN :
0-8186-8005-9
DOI :
10.1109/HOST.1997.613497