Hyperspectral Gaussian Filtering : Edge-Preserving Smoothing for Hyperspectral Image and Its Separable Acceleration

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For hyperspectral imaging, we proposed an edge-preserving filter, named hyperspectral Gaussian filtering, and its separable implementation for accelerating the proposed filter. Experimental results show that the acceleration has superior performance to the brute-force implementation and the other state-of-the-art methods in denosing. Also, we successfully achieves 70-times speedup with the acceleration.

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