A detection statistic for random-valued impulse noise

Yiqiu DONG; Raymond H. CHAN; Shufang XU

doi:10.1109/TIP.2006.891348

A detection statistic for random-valued impulse noise

Yiqiu DONG^*, Raymond H. CHAN, Shufang XU

^*Corresponding author for this work

Research output: Journal Publications › Journal Article (refereed) › peer-review

252 Citations (Scopus)

Abstract

This paper proposes an image statistic for detecting random-valued impulse noise. By this statistic, we can identify most of the noisy pixels in the corrupted images. Combining it with an edge-preserving regularization, we obtain a powerful two-stage method for denoising random-valued impulse noise, even for noise levels as high as 60%. Simulation results show that our method is significantly better than a number of existing techniques in terms of image restoration and noise detection.

Original language	English
Pages (from-to)	1112-1120
Number of pages	9
Journal	IEEE Transactions on Image Processing
Volume	16
Issue number	4
DOIs	https://doi.org/10.1109/TIP.2006.891348
Publication status	Published - Apr 2007
Externally published	Yes

Funding

Manuscript received February 28, 2006; revised October 21, 2006. This work was supported in part by RFDP (20030001103), in part by the NSFC (10571007) of China, and in part by HKRGC Grants CUHK 400503 and CUHK DAG 2060257. The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Stanley J. Reeves.

Keywords

Edge-preserving regularization
Image denoising
Noise detector
Random-valued impulse noise

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10.1109/TIP.2006.891348

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AB - This paper proposes an image statistic for detecting random-valued impulse noise. By this statistic, we can identify most of the noisy pixels in the corrupted images. Combining it with an edge-preserving regularization, we obtain a powerful two-stage method for denoising random-valued impulse noise, even for noise levels as high as 60%. Simulation results show that our method is significantly better than a number of existing techniques in terms of image restoration and noise detection.

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A detection statistic for random-valued impulse noise

Abstract

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Keywords

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