Image identification and restoration in the subband domain

Author

Kim, Jaemin ; Woods, John W.

Author_Institution

Dept. of Electr. Comput. & Syst. Eng., Rensselaer Polytech. Inst., Troy, NY, USA

Volume

3

Issue

3

fYear

1994

fDate

5/1/1994 12:00:00 AM

Firstpage

312

Lastpage

314

Abstract

When faced with a large support point spread function (PSF), the iterative expectation-maximization (EM) algorithm, which is often used for PSF identification, is very sensitive to the initial PSF estimate. To deal with this problem, the authors propose to do EM image identification and restoration in the subband domain. After the image is first divided into subbands, the EM algorithm is applied to each subband separately. Since the PSF can be taken to have smaller support in each subband, these subbands should be less of a problem with the EM model identification. They also introduce an adaptive subband EM method for use in the upper frequency subbands

Keywords

image reconstruction; image segmentation; iterative methods; optical transfer function; EM algorithm; adaptive subband EM method; image identification; image restoration; iterative expectation-maximization algorithm; point spread function; subband domain; upper frequency subbands; Degradation; Equations; Frequency; Image converters; Image processing; Image restoration; Integrated circuit modeling; Iterative algorithms; Systems engineering and theory; Wiener filter;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/83.287026

Filename

287026