Title :
Statistical imaging and complexity regularization
Author :
Moulin, Pierre ; Liu, Juan
Author_Institution :
Beckman Inst. for Adv. Sci. & Technol., Illinois Univ., Urbana, IL, USA
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;
Conference_Titel :
Information Theory, 2000. Proceedings. IEEE International Symposium on
Conference_Location :
Sorrento
Print_ISBN :
0-7803-5857-0
DOI :
10.1109/ISIT.2000.866344
