Blur identification from vector quantizer encoder distortion

Author

Panchapakesan, Kannan ; Sheppard, David G. ; Marcellin, Michael W. ; Hunt, Bobby R.

Author_Institution

Dept. of Electr. & Comput. Eng., Arizona Univ., Tucson, AZ, USA

fYear

1998

fDate

4-7 Oct 1998

Firstpage

751

Abstract

A method is presented for image blur identification from vector quantizer (VQ) encoder distortion. The method requires a set of training images produced by each member of a set of candidate blur functions. Each of these sets is then used to train a VQ encoder. Given an image degraded by an unknown blur function, the blur function can be identified by choosing from among the candidates the one corresponding to the VQ encoder with the lowest encoder distortion. Two training methods are investigated: the generalized Lloyd algorithm and a non-iterative discrete cosine transform (DCT)-based approach

Keywords

discrete cosine transforms; image coding; image restoration; vector quantisation; DCT-based approach; VQ encoder; candidate blur functions; generalized Lloyd algorithm; image blur identification; image restoration; non-iterative discrete cosine transform; training images; training methods; vector quantizer encoder distortion; Circuit noise; Degradation; Image restoration; Nonlinear optics; Optical distortion; Optical films; Optical filters; Optical noise; Optical recording; Signal to noise ratio;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1998. ICIP 98. Proceedings. 1998 International Conference on

Conference_Location

Chicago, IL

Print_ISBN

0-8186-8821-1

Type

conf

DOI

10.1109/ICIP.1998.999058

Filename

999058