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Edge-Preserving Filtering of Images with Low Photon Counts
June 2008 (vol. 30 no. 6)
pp. 1014-1027
EEdge-preserving filters such as local M-smoothers or bilateral filtering are usually designed for Gaussian noise. This paper investigates how these filters can be adapted in order to efficiently deal with Poissonian noise. In addition, the issue of photometry invariance is addressed by changing the way filter coefficients are normalized. The proposed normalization is additive, instead of being multiplicative, and leads to a strong connection with anisotropic diffusion. Experiments show that ensuring the photometry invariance leads to comparable denoising performances in terms of the root mean square error computed on the signal.

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Index Terms:
Filtering, Image processing software, Statistical computing
Citation:
John A. Lee, Xavier Geets, Vincent Grégoire, Anne Bol, "Edge-Preserving Filtering of Images with Low Photon Counts," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 30, no. 6, pp. 1014-1027, June 2008, doi:10.1109/TPAMI.2008.16
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