Complexity-regularized denoising of Poisson-corrupted data
Juan Liu
Moulin, P.
Beckman Inst., Illinois Univ., Urbana, IL;
This paper appears in: Image Processing, 2000. Proceedings. 2000 International Conference on
Publication Date: 2000
Volume: 3,
On page(s): 254-257 vol.3
Meeting Date: 09/10/2000 - 09/13/2000
Location: Vancouver, BC, Canada
ISBN: 0-7803-6297-7
References Cited: 13
INSPEC Accession Number: 7005343
Digital Object Identifier: 10.1109/ICIP.2000.899343
Current Version Published: 2002-08-06
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
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