Linear-Quadratic Noise-Smoothing Filters for Quantum-Limited Images

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9 Scopus citations

Abstract

In this correspondence, we consider the use of nonlinear estimators for the noise smoothing of images obtained under quantum-limited imaging conditions. A Volterra expansion is investigated from which a set of linear-quadratic filters is derived using higher order statistics. The filters are applicable for single frame and multiple frames of a single scene imaged under low-light levels.

Original languageEnglish (US)
Pages (from-to)1328-1333
Number of pages6
JournalIEEE Transactions on Image Processing
Volume4
Issue number9
DOIs
StatePublished - Sep 1995

Funding

Various approaches for postprocessing of images degraded by quantum noise have been proposed in the past. Because this type of noise is typically placed into the class of signal-dependent degradations, the majority of these techniques lie in the specification of a nonstationary model for the description of the noise [4], [5], resulting in a genre of nonstationary filters that operate independently at each pixel. This is intuitive with the notion of signal-dependent noise; however, these techniques also have a common feature in that they are linear. PTde it is well known that a nonlinear filter will generally Manuscript received August 18, 1993; revised October 28, 1994. This work was supported in part by a grant from Siemens. The associate editor coordinating the review of this paper and approving it for publication was Dr. Hsueh-Ming Hang.

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design

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