Wavelet-domain filtering for photon imaging systems

Robert Nowak, Richard G. Baraniuk

Research output: Contribution to journalConference article

14 Scopus citations

Abstract

Many imaging systems rely on photon detection as the basis of image formation. One of the major sources of error in these systems is Poisson noise due to the quantum nature of the photon detection process. Unlike additive Gaussian noise, Poisson noise is signal-dependent, and consequently separating signal from noise is a very difficult task. In this paper, we develop a novel wavelet-domain filtering procedure for noise removal in photon imaging systems. The filter adapts to both the signal and the noise and balances the trade-off between noise removal and excessive smoothing of image details. Designed using the statistical method of cross-validation, the filter is simultaneously optimal in a small-sample predictive sum of squares sense and asymptotically optimal in the mean square error sense. The filtering procedure has a simple interpretation as a joint edge detection/estimation process. Moreover, we derive an efficient algorithm for performing the filtering that has the same order of complexity as the fast wavelet transform itself. The performance of the new filter is assessed with simulated data experiments and tested with actual nuclear medicine imager.

Original languageEnglish (US)
Pages (from-to)55-66
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume3169
DOIs
StatePublished - Dec 1 1997
EventWavelet Applications in Signal and Image Processing V - San Diego, CA, United States
Duration: Jul 30 1997Jul 30 1997

Keywords

  • Denoising
  • Photon imaging
  • Poisson processes
  • Wavelets

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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