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28 December 1979 Nonlinear Restoration Of Filtered Images With Poisson Noise
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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.
© (1979) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
C. M. Lo and A. A. Sawchuk "Nonlinear Restoration Of Filtered Images With Poisson Noise", Proc. SPIE 0207, Applications of Digital Image Processing III, (28 December 1979); https://doi.org/10.1117/12.958229
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