Regularization of RIF blind image deconvolution

Author

Ng, Michael K. ; Plemmons, Robert J. ; Sanzheng Qiao

Author_Institution

Dept. of Math., Hong Kong Univ., Hong Kong

Volume

9

Issue

6

fYear

2000

fDate

6/1/2000 12:00:00 AM

Firstpage

1130

Lastpage

1134

Abstract

Blind image restoration is the process of estimating both the true image and the blur from the degraded image, using only partial information about degradation sources and the imaging system. Our main interest concerns optical image enhancement, where the degradation often involves a convolution process. We provide a method to incorporate truncated eigenvalue and total variation regularization into a nonlinear recursive inverse filter (RIF) blind deconvolution scheme first proposed by Kundar, and by Kundur and Hatzinakos (1996, 1998). Tests are reported on simulated and optical imaging problems

Keywords

convolution; deconvolution; image enhancement; image restoration; inverse problems; nonlinear filters; optical information processing; recursive filters; RIF blind image deconvolution; blind image restoration; blur; convolution process; degradation sources; degraded image; imaging system; nonlinear recursive inverse filter blind deconvolution scheme; optical image enhancement; optical imaging; partial information; regularization; total variation regularization; true image; truncated eigenvalue; Convolution; Deconvolution; Degradation; Eigenvalues and eigenfunctions; Image enhancement; Image restoration; Nonlinear optics; Optical filters; Optical imaging; Testing;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/83.846254

Filename

846254