DocumentCode
1275780
Title
Lower bound on average mean-square error for image restoration
Author
Hung, Hsien-Sen
Author_Institution
Dept. of Electr. & Comput. Eng., Iowa State Univ., Ames, IA, USA
Volume
39
Issue
2
fYear
1991
fDate
2/1/1991 12:00:00 AM
Firstpage
497
Lastpage
499
Abstract
An average mean-square error bound that is applicable to general image observation models involving degradations of blur, signal-dependent and signal-independent noise, and sensor nonlinearity is derived. A Cramer-Rao lower bound on average mean-square errors for any unbiased image restoration scheme is derived. This bound is analytically expressed as a function of degradation parameters of imaging systems. Potential performance improvements by incorporating signal-dependent noise or sensor nonlinearity into algorithmic design are discussed
Keywords
interference (signal); picture processing; Cramer-Rao lower bound; algorithmic design; average mean-square error; blur; degradation parameters; image observation models; sensor nonlinearity; signal-dependent noise; signal-independent noise; unbiased image restoration scheme; Covariance matrix; Cramer-Rao bounds; Degradation; Image analysis; Image restoration; Image sensors; Linear matrix inequalities; Parameter estimation; Probability density function; Signal processing;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/78.80837
Filename
80837
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