DocumentCode
2384822
Title
Statistical imaging and complexity regularization
Author
Moulin, Pierre ; Liu, Juan
Author_Institution
Beckman Inst. for Adv. Sci. & Technol., Illinois Univ., Urbana, IL, USA
fYear
2000
fDate
2000
Firstpage
54
Abstract
We apply complexity regularization to statistical ill-posed inverse problems in imaging. We formulate a natural distortion measure in image space and develop nonasymptotic bounds on estimation performance in terms of an index of resolvability that characterizes the compressibility of the true image. These bounds extend previous results that were obtained under simpler observational models
Keywords
computational complexity; data compression; image coding; inverse problems; statistical analysis; complexity regularization; compressibility; distortion measure; estimation performance; image space; index of resolvability; nonasymptotic bounds; statistical ill-posed inverse problems; statistical imaging; AWGN; Additive white noise; Contracts; Distortion measurement; Extraterrestrial measurements; Gaussian noise; Image coding; Image resolution; Inverse problems; Ultrasonic imaging;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory, 2000. Proceedings. IEEE International Symposium on
Conference_Location
Sorrento
Print_ISBN
0-7803-5857-0
Type
conf
DOI
10.1109/ISIT.2000.866344
Filename
866344
Link To Document