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Autocorrelation-Driven Diffusion Filtering
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DOI：10.1109/TIP.2011.2107330.png)
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Abstract
En 中文
In this paper, we present a novel scheme for anisotropic diffusion driven by the image autocorrelation function. We show the equivalence of this scheme to a special case of iterated adaptive filtering. By determining the diffusion tensor field from an autocorrelation estimate, we obtain an evolution equation that is computed from a scalar product of diffusion tensor and the image Hessian. We propose further a set of filters to approximate the Hessian on a minimized spatial support. On standard benchmarks, the resulting method performs favorable in many cases, in particular at low noise levels. In a GPU implementation, video real-time performance is easily achieved.
Keywords:
Adaptive filtering
diffusion filtering
image enhancement
steerable filters
structure tensor
Journal
IF:
13.7
Papers:
1.0W
Citations:
8.4W
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