Adaptive Nonlocal Filtering: A Fast Alternative to Anisotropic Diffusion for Image Enhancement
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Abstract—Nonlinear anisotropic diffusion algorithms provide significant improvement in image enhancement as compared to linear filters. However, the excessive computational cost of solving nonlinear PDEs precludes their use in real-time vision applications. In the present paper, we show that two orders of magnitude speed improvement is provided by a new image filtering paradigm in which an adaptively determined vector field specifies nonlocal application points for an image filter.
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Index Terms:
Segmentation, diffusion, scale-space, anisotropic diffusion, nonlinear diffusion, filtering, permutation filter, nonlocal filter.
Citation:
Bruce Fischl, Eric L. Schwartz, "Adaptive Nonlocal Filtering: A Fast Alternative to Anisotropic Diffusion for Image Enhancement," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 21, no. 1, pp. 42-48, Jan. 1999, doi:10.1109/34.745732
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