A vector quantizer for image restoration

Author

Sheppard, David G. ; Bilgin, Ali ; Nadar, Mariappan S. ; Hunt, Bobby R. ; Marcellin, Michael W.

Author_Institution

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

Volume

7

Issue

1

fYear

1998

fDate

1/1/1998 12:00:00 AM

Firstpage

119

Lastpage

124

Abstract

This paper presents a novel technique for image restoration based on nonlinear interpolative vector quantization (NLIVQ). The algorithm performs nonlinear restoration of diffraction-limited images concurrently with quantization. It is trained on image pairs consisting of an original image and its diffraction-limited counterpart. The discrete cosine transform is used in the codebook design process to control complexity. Simulation results are presented that demonstrate improvements in visual quality and peak signal-to-noise ratio of the restored images

Keywords

discrete cosine transforms; image coding; image restoration; interpolation; source coding; transform coding; vector quantisation; DCT; block source coding; codebook design; complexity control; diffraction-limited images; discrete cosine transform; image pairs; image restoration; nonlinear interpolative vector quantization; nonlinear restoration; peak signal-to-noise ratio; simulation results; vector quantizer; visual quality; Discrete cosine transforms; Image coding; Image processing; Image restoration; Interpolation; Kernel; Optical distortion; Optical signal processing; Signal processing algorithms; Vector quantization;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/83.650857

Filename

650857