Spectral Spatial Variation.

Automatic carcinoma detection from hyper/multi spectral images is of essential importance due to the fact that these images cannot be presented directly to the clinician. However, standard approaches for carcinoma detection use hundreds or even thousands of features. This would cost a high amount of RAM (random access memory) for a pixel wise analysis and would slow down the classification or make it even impossible on standard PCs.