A rigid POCS extension to a Poisson super-resolution algorithm

Author

Keightley, D. ; Hunt, B.R.

Author_Institution

Div. of Inf. Technol., CSIRO, Canberra, ACT, Australia

Volume

2

fYear

1995

fDate

23-26 Oct 1995

Firstpage

508

Abstract

A model-based iterative Poisson maximum aposteriori (MAP) algorithm is extended to include a rigid projection on convex sets (POCS) step. Such an extension yields a significantly faster convergence to a perceptually and measurably better estimate of a class of objects. Both the MAP and POCS approaches have been shown to be highly successful at incorporating prior knowledge into nonlinear restoration schemes. This work shows a method for improving the restoration capabilities of an iterative MAP deconvolution technique by using spatial constraints in a POCS enhancement which shrinks the space of feasible solutions and suggests directions for future refinements

Keywords

convergence of numerical methods; deconvolution; image enhancement; image resolution; image restoration; iterative methods; maximum likelihood estimation; stochastic processes; POCS enhancement; Poisson superresolution algorithm; convergence; iterative MAP deconvolution technique; iterative Poisson maximum aposteriori algorithm; model based MAP algorithm; nonlinear restoration schemes; projection on convex sets; rigid POCS extension; spatial constraints; Additive noise; Frequency; Image restoration; Iterative algorithms; Noise shaping; Nonlinear optics; Optical attenuators; Optical imaging; Optical noise; Shape;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1995. Proceedings., International Conference on

Conference_Location

Washington, DC

Print_ISBN

0-8186-7310-9

Type

conf

DOI

10.1109/ICIP.1995.537527

Filename

537527