IEEE International Conference on Image Processing 2005 2005
DOI: 10.1109/icip.2005.1529696
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Homogeneity-based directional sigma filtering of video noise

Abstract: This paper proposes a real-time method for the reduction of white Gaussian video noise. The method achieves a maximum gain of 4.8 dB and is capable of preserving image content. It adapts window size, weighting and behavior to both image content and noise level in order to optimize the filtering. It starts by detecting the intensity-homogeneous direction from 8 different candidates. A variant of the Sigma filter is then applied directionally. The filtering is performed along homogeneous areas and not across edg… Show more

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Cited by 7 publications
(2 citation statements)
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“…Reference [2] cited numbers of image denoising algorithms, and the most typical are mean filters and median filters, which lead to many variations [3][4] [5]. The implementation of such algorithms is simple, but the effect of denoising is not satisfying.…”
Section: A Analysis Ofnoise Reduction For Surveillance Videomentioning
confidence: 99%
“…Reference [2] cited numbers of image denoising algorithms, and the most typical are mean filters and median filters, which lead to many variations [3][4] [5]. The implementation of such algorithms is simple, but the effect of denoising is not satisfying.…”
Section: A Analysis Ofnoise Reduction For Surveillance Videomentioning
confidence: 99%
“…Many video denoising algorithms have been proposed in literature and they may be classified as spatial domain methods [3][4][5][6] and transform domain methods [7][8][9][10][11][12][13]. In realtime video encoding system, the computational complexity of the wavelet domain method is too high.…”
Section: Introductionmentioning
confidence: 99%