CPC G01J 3/2823 (2013.01) [G01J 3/0202 (2013.01); G01J 3/0208 (2013.01); G01J 3/0237 (2013.01); G01J 3/0264 (2013.01); G01J 3/0286 (2013.01); G01J 3/0291 (2013.01); G01J 3/28 (2013.01); G06F 18/214 (2023.01); G06F 18/24 (2023.01); H04N 23/11 (2023.01); H04N 23/51 (2023.01); H04N 23/71 (2023.01); H04N 23/73 (2023.01); G01J 2003/2826 (2013.01)] | 8 Claims |
1. A method of processing a series of hyperspectral images in order to classify its constituent parts, the method including the steps of:
(a) deriving a non-stationary observation angle dependent probabilistic model having a series of parameters for the series of hyperspectral images;
(b) training the series of probabilistic model parameters on mineral samples obtained from artificial light reflectance measurements; and
(c) utilising the probabilistic model on hyperspectral imagery acquired from sampling geographical conditions under natural lighting conditions, to classify constituent parts of the hyperspectral imagery.
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