Statistics in bilateral domain: Novel statistics of natural images

Recently, there has been a great deal of interest in statistics of natural images in linear domain. However, a detail study of image statistics in non-linear domain on a very large dataset is still missing. In this paper, we analyze natural images' statistics in “bilateral domain” on different sub bands which are generated by the classical bilateral filter. Compared with those in linear domain, the statistics in bilateral domain are significantly superior in generalization, de-correlation, and local feature extraction. We also observe some entirely new but interesting features.

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