Restoration of randomly blurred images via the maximum a posteriori criterion

Author

Guan, Ling ; Ward, Rabab K.

Author_Institution

Dept. of Electr. Eng., British Columbia Univ., Vancouver, BC, Canada

Volume

1

Issue

2

fYear

1992

fDate

4/1/1992 12:00:00 AM

Firstpage

256

Lastpage

262

Abstract

The maximum a posteriori (MAP) estimation technique is applied to the problem of restoring images distorted by noisy point spread functions and additive noise. The resulting MAP estimator is nonlinear and is obtained by numerically maximizing a conditional probability density function. The energy nonnegativity constraint is incorporated in the optimization process. Although the deblurring results are slightly inferior to those obtained by applying the Wiener criterion, the advantage of the MAP estimator lies in its significant suppression of noise

Keywords

interference suppression; picture processing; MAP estimator; additive noise; conditional probability density function; energy nonnegativity constraint; image restoration; maximum a posteriori criterion; maximum a posteriori estimation; noise suppression; noisy point spread functions; nonlinear estimator; optimization process; randomly blurred images; Additive noise; Additive white noise; Concatenated codes; Constraint optimization; Equations; Image restoration; Maximum a posteriori estimation; Nonlinear distortion; PSNR; Probability density function;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/83.136603

Filename

136603