Refinement of EM restored images using adaptive POCS

Author

Kuo, Shyh-Shiaw ; Mammone, Richard J.

Author_Institution

Dept. of Electr. & Comput. Eng., Rutgers Univ., Piscataway, NJ, USA

fYear

1991

fDate

14-17 Apr 1991

Firstpage

2925

Abstract

A new iterative algorithm for image restoration and point spread function (PSF) estimation is presented. The method initially restores the image with the expectation maximization (EM) algorithm. The resulting estimate is then significantly improved by using the adaptive row action projection (RAP) algorithm which is based on the theory of projection onto convex sets (POCS). The PSF is re-estimated using a least squares technique. Computer simulations show the method´s competitiveness in restoring degraded images and estimating the PSF from noisy blurred images with unknown PSF

Keywords

estimation theory; iterative methods; least squares approximations; optical transfer function; optimisation; picture processing; set theory; EM restored images; PSF estimation; adaptive POCS; adaptive row action projection algorithm; expectation maximisation algorithm; iterative algorithm; least squares technique; noisy blurred images; point spread function; projection onto convex sets; restored image refinement; Computer simulation; Convolution; Degradation; Equations; Fitting; Image restoration; Iterative algorithms; Least squares methods; Maximum likelihood estimation; Noise measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference on

Conference_Location

Toronto, Ont.

ISSN

1520-6149

Print_ISBN

0-7803-0003-3

Type

conf

DOI

10.1109/ICASSP.1991.151015

Filename

151015