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Affine non-local Bayesian image denoising algorithm
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AI
DOI：10.1007/s00371-021-02316-x.png)
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Abstract
En 中文
This paper proposes an extension of the non-local Bayesian denoising algorithm. The idea is to use elliptical patches instead of regular square patches in the grouping process. We calculate the elliptical patches by an iterative method. We then use an affine invariant patch similarity measure to calculate the distance between two elliptical patches. Since the elliptical patch is a shape-adaptive patch and this similarity measure performs a patch comparison by automatically adapting the size and shape of the patches, so more similar patches are found and used for image denoising. This algorithm denoising procedure goes through two identical iterations to further improve the denoising performance. Experimental results on test images demonstrate that this algorithm achieves state-of-the-art denoising performance in terms of numerical results and subjective visual quality, compared with the non-local Bayesian.
Keywords:
Elliptical patches
Affine invariant patch similarity measure
Bayesian
Image denoising
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