Image deconvolution using wavelet-based regularization

Lixin Shen

doi:10.1117/1.1426386

Image deconvolution using wavelet-based regularization

Lixin Shen

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

2 Scopus citations

Abstract

In this paper, we propose a wavelet-based regularization algorithm for image deconvolution problems whose blurring filter is a low pass filter of an M-band wavelet. The perfect reconstruction formula of this M-band wavelet is used to establish our wavelet-based regularization algorithm. The simulations shew that our proposed algorithm for image deconvolution performs better than that of the Wiener filter and some other wavelet-based deconvolution algorithms in terms of the improvement in signal-to-noise ratio.

Original language	English (US)
Pages (from-to)	5-10
Number of pages	6
Journal	Journal of Electronic Imaging
Volume	11
Issue number	1
DOIs	https://doi.org/10.1117/1.1426386
State	Published - Jan 2002
Externally published	Yes

ASJC Scopus subject areas

Atomic and Molecular Physics, and Optics
Computer Science Applications
Electrical and Electronic Engineering

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author = "Lixin Shen",

note = "Funding Information: This work was supported by the Center for Wavelets, Approximation and Information Processing (CWAIP) which is funded by the National Science and Technology Board and the Ministry of Education under Grant No. RP960 601/A, and the National University of Singapore.",

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AB - In this paper, we propose a wavelet-based regularization algorithm for image deconvolution problems whose blurring filter is a low pass filter of an M-band wavelet. The perfect reconstruction formula of this M-band wavelet is used to establish our wavelet-based regularization algorithm. The simulations shew that our proposed algorithm for image deconvolution performs better than that of the Wiener filter and some other wavelet-based deconvolution algorithms in terms of the improvement in signal-to-noise ratio.

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Image deconvolution using wavelet-based regularization

Abstract

ASJC Scopus subject areas

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