Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization

Raymond H. CHAN; Chung Wa HO; Mila NIKOLOVA

doi:10.1109/TIP.2005.852196

Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization

Raymond H. CHAN^*, Chung Wa HO, Mila NIKOLOVA

^*Corresponding author for this work

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

931 Citations (Scopus)

Abstract

This paper proposes a two-phase scheme for removing salt-and-pepper impulse noise. In the first phase, an adaptive median filter is used to identify pixels which are likely to be contaminated by noise (noise candidates). In the second phase, the image is restored using a specialized regularization method that applies only to those selected noise candidates. In terms of edge preservation and noise suppression, our restored images show a significant improvement compared to those restored by using just nonlinear filters or regularization methods only. Our scheme can remove salt-and-pepper-noise with a noise level as high as 90%.

Original language	English
Pages (from-to)	1479-1485
Number of pages	7
Journal	IEEE Transactions on Image Processing
Volume	14
Issue number	10
Early online date	19 Sept 2005
DOIs	https://doi.org/10.1109/TIP.2005.852196
Publication status	Published - Oct 2005
Externally published	Yes

Funding

This work was supported by HKRGC under Grant CUHK4243/01P and CUHK DAG 2060220. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Thierry Blu.

Keywords

Adaptive median filter
Edge-preserving regularization
Impulse noise

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10.1109/TIP.2005.852196

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AB - This paper proposes a two-phase scheme for removing salt-and-pepper impulse noise. In the first phase, an adaptive median filter is used to identify pixels which are likely to be contaminated by noise (noise candidates). In the second phase, the image is restored using a specialized regularization method that applies only to those selected noise candidates. In terms of edge preservation and noise suppression, our restored images show a significant improvement compared to those restored by using just nonlinear filters or regularization methods only. Our scheme can remove salt-and-pepper-noise with a noise level as high as 90%.

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Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization

Abstract

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Keywords

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