Khuwuthyakorn, Pattaraporn; Robles-Kelly, Antonio; Zhou, Jun
In this paper, we address the problem of recovering a hyperspectral texture descriptor. We do this by viewing the wavelength-indexed bands corresponding to the texture in the image as those arising from a stochastic process whose statistics can be captured making use of the relationships between moment generating functions and Fourier kernels. In this manner, we can interpret the probability distribution of the hyperspectral texture as a heavy-tailed one which can be rendered invariant to...[Show more]
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