A vector quantizer for image restoration

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 di...

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Bibliographic Details
Published inIEEE transactions on image processing Vol. 7; no. 1; pp. 119 - 124
Main Authors Sheppard, D.G., Bilgin, A., Nadar, M.S., Hunt, B.R., Marcellin, M.W.
Format Journal Article
LanguageEnglish
Published New York, NY IEEE 01.01.1998
Institute of Electrical and Electronics Engineers
Subjects
Applied sciences
Discrete cosine transforms
Exact sciences and technology
Image coding
Image processing
Image restoration
Information, signal and communications theory
Interpolation
Kernel
Optical distortion
Optical signal processing
Signal processing
Signal processing algorithms
Telecommunications and information theory
Vector quantization
Interpolation
Vector quantization
Image processing
Image restoration
Non linear processing
Algorithm
Cosine transform
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Summary: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.
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ISSN:1057-7149
1941-0042
DOI:10.1109/83.650857