Title :
Complexity-regularized denoising of Poisson-corrupted data
Author :
Liu, Juan ; Moulin, Pierre
Author_Institution :
Beckman Inst., Illinois Univ., Urbana, IL, USA
Abstract :
We apply the complexity-regularization principle to Poisson imaging. We formulate a natural distortion measure in the image space, and present a connection between complexity-regularized estimation and rate-distortion theory. For computational tractability, we apply constrained coders such as JPEG or SPIHT to solve the optimization problem approximately. Also, we design a simple predictive coder which lends itself well to our optimization problem
Keywords :
computational complexity; image coding; image processing; optimisation; prediction theory; rate distortion theory; stochastic processes; 2D median filter predictor; JPEG; MDL estimator; Poisson imaging; Poisson-corrupted data; SPIHT; complexity-regularized denoising; complexity-regularized estimation; computational tractability; constrained coders; image space; natural distortion measure; optimization problem solution; predictive coding algorithms; rate-distortion theory; Constraint optimization; Design optimization; Distortion measurement; Entropy; Extraterrestrial measurements; Image resolution; Magnetic resonance imaging; Noise reduction; Performance loss; Rate-distortion;
Conference_Titel :
Image Processing, 2000. Proceedings. 2000 International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-6297-7
DOI :
10.1109/ICIP.2000.899343
