Fusion of radiometry and textural information for SIR-C image classification

We consider the problem of multi-channel image classification. We take into account not only the radiometric information but also some textural information. The proposed algorithm is a particular case of a fission-fusion scheme. The fission step consists of defining some textural parameters and extracting them from the different channels. The fusion between the texture channels and the original radiometric channels is performed in a second step. We consider a supervised scheme in which some training areas are given. These training areas allow us to define the class parameters and to drive the fusion process. Some results are given on SIR-C images.