DocumentCode
3094056
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
fYear
1997
fDate
21-23 Jul 1997
Firstpage
108
Lastpage
111
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Higher-Order Statistics, 1997., Proceedings of the IEEE Signal Processing Workshop on
Conference_Location
Banff, Alta.
Print_ISBN
0-8186-8005-9
Type
conf
DOI
10.1109/HOST.1997.613497
Filename
613497
Link To Document