A dynamical model to classify the content of multitemporal images employing distributed computing techniques

An intelligent post-processing paradigm based on the use of a dynamical filtering technique modified to enhance the reconstruction quality of remote sensing indexes using multitemporal images and distributed computing techniques is proposed. As a matter of particular study, a robust algorithm is reported for the analysis of the dynamic behavior of geophysical signatures extracted from remotely sensed scenes. The simulation results prove the efficiency of the proposed technique along with the computational implementation based on a big-data framework using distributed processing.