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Data · dataset · 2018

Autocorrelation-Driven Diffusion Filtering

Listed in Researchdata.se

The dataset consists of Matlab code and present a novel scheme for anisotropic diffusion driven by the image autocorrelation function.

Description

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.

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The dataset was originally published in DiVA and moved to SND in 2024.

Links

Where it is published

Catalogue records · 1

Topics

Inferred from text
Computational imaging 78% · Image 75% · Video 75%
Provenance · 1 source records, 10 field assertions
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Researchdata.seoai:researchdata.se:2024-219/112 d agoJSON v1
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