Multiple resolution image restoration

A. W.C. Liew; Ngai Fong Law; D. T. Nguyen

doi:10.1049/ip-vis:19971045

Multiple resolution image restoration

A. W.C. Liew, Ngai Fong Law, D. T. Nguyen

Research output: Journal article publication › Journal article › Academic research › peer-review

6 Citations (Scopus)

Abstract

A new algorithm for solving the deconvolution problem is proposed. This algorithm uses the wavelet transform to induce a multiresolution approach to deconvolve a blurred signal/image. The low resolution part of a signal/ image is restored first and then high resolution information is added successively into the estimation process. Two 'different ways to incorporate the image space positivity constraint, namely loosely and strictly, are discussed. In contrast to most restoration algorithms, the positivity constraint is applied directly in the transformed domain. The performance of the algorithm in the presence of noise is also investigated.

Original language	English
Pages (from-to)	199-206
Number of pages	8
Journal	IEE Proceedings: Vision, Image and Signal Processing
Volume	144
Issue number	4
DOIs	https://doi.org/10.1049/ip-vis:19971045
Publication status	Published - 1 Jan 1997
Externally published	Yes

Keywords

Image processing
Wavelet transform

ASJC Scopus subject areas

Signal Processing
Electrical and Electronic Engineering

More information

10.1049/ip-vis:19971045

Cite this

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AU - Law, Ngai Fong

AU - Nguyen, D. T.

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N2 - A new algorithm for solving the deconvolution problem is proposed. This algorithm uses the wavelet transform to induce a multiresolution approach to deconvolve a blurred signal/image. The low resolution part of a signal/ image is restored first and then high resolution information is added successively into the estimation process. Two 'different ways to incorporate the image space positivity constraint, namely loosely and strictly, are discussed. In contrast to most restoration algorithms, the positivity constraint is applied directly in the transformed domain. The performance of the algorithm in the presence of noise is also investigated.

AB - A new algorithm for solving the deconvolution problem is proposed. This algorithm uses the wavelet transform to induce a multiresolution approach to deconvolve a blurred signal/image. The low resolution part of a signal/ image is restored first and then high resolution information is added successively into the estimation process. Two 'different ways to incorporate the image space positivity constraint, namely loosely and strictly, are discussed. In contrast to most restoration algorithms, the positivity constraint is applied directly in the transformed domain. The performance of the algorithm in the presence of noise is also investigated.

KW - Image processing

KW - Wavelet transform

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U2 - 10.1049/ip-vis:19971045

DO - 10.1049/ip-vis:19971045

M3 - Journal article

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JF - IEE Proceedings: Vision, Image and Signal Processing

IS - 4

ER -

Multiple resolution image restoration

Abstract

Keywords

ASJC Scopus subject areas

More information

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