A vector quantizer for image restoration

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

doi:10.1109/83.650857

A vector quantizer for image restoration

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

Research output: Contribution to journal › Article › peer-review

21 Scopus citations

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.

Original language	English (US)
Pages (from-to)	119-124
Number of pages	6
Journal	IEEE Transactions on Image Processing
Volume	7
Issue number	1
DOIs	https://doi.org/10.1109/83.650857
State	Published - 1998

Keywords

Image restoration
Nonlinear image processing
Nonlinear interpolation
Vector quantization

ASJC Scopus subject areas

Software
Computer Graphics and Computer-Aided Design

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10.1109/83.650857

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keywords = "Image restoration, Nonlinear image processing, Nonlinear interpolation, Vector quantization",

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year = "1998",

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AU - Bilgin, Ali

AU - Nadar, Mariappan S.

AU - Hunt, Bobby R.

AU - Marcellin, Michael W.

PY - 1998

Y1 - 1998

N2 - 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.

AB - 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.

KW - Image restoration

KW - Nonlinear image processing

KW - Nonlinear interpolation

KW - Vector quantization

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A vector quantizer for image restoration

Abstract

Keywords

ASJC Scopus subject areas

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