Mixed pixel decomposition of satellite images based on source separation method

In this paper we propose to prove the importance of the application of blind source separation methods on remote sensing data. Satellite images are represented by radiometric value that can be considered as a mixture of independent sources. To restore the independent sources we use the statistical method of Joint Approximate Diagonalization of Eigen-matrix (JADE). The proposed algorithm generates source images where each one gives a maximum of information specific to a certain type of land cover. These source images do not provide one scalar value per pixel, but rather a vector which components will agree with the radiometric value of the different land cover types present in the pixel.