Image Analysis Under Varying Illumination

Often in dealing with images, the training data must be extracted for a limited data set. In particular, the illumination conditions of the sample images is limited and, in many cases, unknown. In this paper, we show that artificial variation of the illuminant of hyperspectral images can be used to overcome the limitations of a small sample set.