Hyperspectral Image Enhancement using Diffusion and Shock Filtering Techniques

We propose a novel method for hyperspectral image filtering and enhancement. The method is developed under the Partial Differential Equations framework and has good noise filtering, details preservation and enhancement capabilities. Its efficiency is proven both in terms of visual means and in terms of overall classification accuracy obtained on several public hyperspectral image data sets, by integration of the method as a preprocessing step.

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