Fast image restoration methods for impulse and Gaussian noises removal

Yu Mei Huang; Kwok Po Ng; You Wei Wen

doi:10.1109/LSP.2009.2016835

Fast image restoration methods for impulse and Gaussian noises removal

Yu Mei Huang^*, Kwok Po Ng, You Wei Wen

^*Corresponding author for this work

Department of Mathematics

Research output: Contribution to journal › Journal article › peer-review

65 Citations (Scopus)

Abstract

In this paper, we study the restoration of blurred images corrupted by impulse noise or mixed impulse plus Gaussian noises. In the proposed method, we use the modified total variation minimization scheme to regularize the deblurred image and fill in suitable values for noisy image pixels where these are detected by median-type filters. An alternating minimization algorithm is employed to solve the proposed total variation minimization problem. Our experimental results show the proposed algorithm is very efficient and the quality of restored images by the proposed method is competitive with those restored by the existing variational image restoration methods.

Original language	English
Pages (from-to)	457-460
Number of pages	4
Journal	IEEE Signal Processing Letters
Volume	16
Issue number	6
DOIs	https://doi.org/10.1109/LSP.2009.2016835
Publication status	Published - Jun 2009

Scopus Subject Areas

Signal Processing
Electrical and Electronic Engineering
Applied Mathematics

User-Defined Keywords

Deblurring
Denoising
Gaussian noise
Impulse noise
Total variation

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10.1109/LSP.2009.2016835

Cite this

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title = "Fast image restoration methods for impulse and Gaussian noises removal",

abstract = "In this paper, we study the restoration of blurred images corrupted by impulse noise or mixed impulse plus Gaussian noises. In the proposed method, we use the modified total variation minimization scheme to regularize the deblurred image and fill in suitable values for noisy image pixels where these are detected by median-type filters. An alternating minimization algorithm is employed to solve the proposed total variation minimization problem. Our experimental results show the proposed algorithm is very efficient and the quality of restored images by the proposed method is competitive with those restored by the existing variational image restoration methods.",

keywords = "Deblurring, Denoising, Gaussian noise, Impulse noise, Total variation",

author = "Huang, {Yu Mei} and Ng, {Kwok Po} and Wen, {You Wei}",

note = "Funding Information: Manuscript received September 10, 2008; revised January 14, 2009. Current version published April 24, 2009. This work was supported in part by RGC 201508 and HKBU FRGs and also by NSFC Grants 60702030, 10871075, 40830424 and the Wavelets and Information Processing Program under a grant from DSTA, Singapore. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Lap-Pui Chau.",

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AU - Huang, Yu Mei

AU - Ng, Kwok Po

AU - Wen, You Wei

N1 - Funding Information: Manuscript received September 10, 2008; revised January 14, 2009. Current version published April 24, 2009. This work was supported in part by RGC 201508 and HKBU FRGs and also by NSFC Grants 60702030, 10871075, 40830424 and the Wavelets and Information Processing Program under a grant from DSTA, Singapore. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Lap-Pui Chau.

PY - 2009/6

Y1 - 2009/6

N2 - In this paper, we study the restoration of blurred images corrupted by impulse noise or mixed impulse plus Gaussian noises. In the proposed method, we use the modified total variation minimization scheme to regularize the deblurred image and fill in suitable values for noisy image pixels where these are detected by median-type filters. An alternating minimization algorithm is employed to solve the proposed total variation minimization problem. Our experimental results show the proposed algorithm is very efficient and the quality of restored images by the proposed method is competitive with those restored by the existing variational image restoration methods.

AB - In this paper, we study the restoration of blurred images corrupted by impulse noise or mixed impulse plus Gaussian noises. In the proposed method, we use the modified total variation minimization scheme to regularize the deblurred image and fill in suitable values for noisy image pixels where these are detected by median-type filters. An alternating minimization algorithm is employed to solve the proposed total variation minimization problem. Our experimental results show the proposed algorithm is very efficient and the quality of restored images by the proposed method is competitive with those restored by the existing variational image restoration methods.

KW - Deblurring

KW - Denoising

KW - Gaussian noise

KW - Impulse noise

KW - Total variation

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DO - 10.1109/LSP.2009.2016835

M3 - Journal article

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EP - 460

JO - IEEE Signal Processing Letters

JF - IEEE Signal Processing Letters

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Fast image restoration methods for impulse and Gaussian noises removal

Abstract

Scopus Subject Areas

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