An enhanced NAS-RIF algorithm for blind image deconvolution

Author

Ong, Chin Ann ; Chambers, Jonathon A.

Author_Institution

Dept. of Electr. & Electron. Eng., Imperial Coll. of Sci., Technol. & Med., London, UK

Volume

8

Issue

7

fYear

1999

fDate

7/1/1999 12:00:00 AM

Firstpage

988

Lastpage

992

Abstract

We enhance the performance of the nonnegativity and support constraints recursive inverse filtering (NAS-RIF) algorithm for blind image deconvolution. The original cost function is modified to overcome the problem of operation on images with different scales for the representation of pixel intensity levels. Algorithm resetting is used to enhance the convergence of the conjugate gradient algorithm. A simple pixel classification approach is used to automate the selection of the support constraint. The performance of the resulting enhanced NAS-RIF algorithm is demonstrated on various images

Keywords

conjugate gradient methods; convergence of numerical methods; deconvolution; image classification; image representation; inverse problems; recursive filters; algorithm resetting; blind image deconvolution; conjugate gradient algorithm; convergence; cost function; enhanced NAS-RIF algorithm; nonnegativity and support constraints recursive inverse filtering; performance; pixel classification approach; pixel intensity levels; representation; scales; Additive noise; Biomedical imaging; Convergence; Cost function; Deconvolution; Degradation; Filtering algorithms; Finite impulse response filter; Pixel; Signal processing algorithms;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/83.772250

Filename

772250