Genetic programming and one-class classification for discovering useful spectral transformations

This work presents a new approach for automatic discovering of useful spectral transformations in remotely sensed imagery. The method applies an approach based on One-class classification, ISODATA unsupervised classification and Genetic Programming (GP) to combine spectral bands. Experiments on burned areas extraction from Landsat8-Oli images show that the proposed method yields better results than the traditional spectral transformations.