Statistical imaging and complexity regularization

P. Moulin, J. Liu

Research output: Contribution to journalConference articlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)54
Number of pages1
JournalIEEE International Symposium on Information Theory - Proceedings
StatePublished - 2000
Event2000 IEEE International Symposium on Information Theory - Serrento, Italy
Duration: Jun 25 2000Jun 30 2000

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics


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