Complexity-regularized denoising of poisson-corrupted data

J. Liu, P. Moulin

Research output: Contribution to conferencePaperpeer-review


In this paper, we apply the complexity-regularization principle to Poisson imaging. We formulate a natural distortion measure in 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.

Original languageEnglish (US)
StatePublished - 2000
EventInternational Conference on Image Processing (ICIP 2000) - Vancouver, BC, Canada
Duration: Sep 10 2000Sep 13 2000


OtherInternational Conference on Image Processing (ICIP 2000)
CityVancouver, BC

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering


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