Recursive enhancement of noncausal images

Author

Balram, Nikhil ; Moura, José M F

Author_Institution

Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA

fYear

1991

fDate

14-17 Apr 1991

Firstpage

2997

Abstract

A recursive procedure is implemented for the enhancement of noncausal Gauss Markov random fields. Experimental results for the enhancement of synthetic as well as real images corrupted by additive white Gaussian noise are provided. These are contrasted with equivalent results obtained by processing the images with recursive filters derived by imposing a causality constraint upon the fields. The results show that the noncausal recursors provide considerable reduction in the mean square error (MSE) of the noisy images without the introduction of undesirable visual effects, such as streaking, that are produced when causality constraints are imposed

Keywords

Markov processes; picture processing; white noise; additive white Gaussian noise; causality constraint; image processing; mean square error; noisy images; noncausal Gauss Markov random fields; noncausal images; noncausal recursors; recursive filters; recursive image enhancement; Additive white noise; Covariance matrix; Filters; Gaussian processes; Lattices; Markov random fields; Maximum likelihood estimation; Mean square error methods; Noise reduction; Visual effects;

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.1991.151033

Filename

151033