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Proceedings Paper

Nonlinear Restoration Of Filtered Images With Poisson Noise
Author(s): C. M. Lo; A. A. Sawchuk
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Paper Abstract

A model for photon resolved low light level image signals detected by a counting array is developed. Those signals are impaired by signal dependent Poisson noise and linear blurring. An optimal restoration filter based on maximizing the a posteriori probability density (MAP) is developed. A suboptimal overlap-save sectioning method using a Newton-Raphson iterative procedure is used for the solution of the high dimensionality nonlinear estimation equations for any type of space-variant and invariant linear blur. An accurate image model with a nonstationary mean and stationary variance is used to provide a priori information for the MAP restoration filter. Finally, a comparison between the MAP filter and a linear space-invariant minimum mean-square error (LMMSE) filter is made.

Paper Details

Date Published: 28 December 1979
PDF: 12 pages
Proc. SPIE 0207, Applications of Digital Image Processing III, (28 December 1979); doi: 10.1117/12.958229
Show Author Affiliations
C. M. Lo, Northrop Corporation (United States)
A. A. Sawchuk, University of Southern California (United States)

Published in SPIE Proceedings Vol. 0207:
Applications of Digital Image Processing III
Andrew G. Tescher, Editor(s)

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