Use of Neural Networks in Multi-Sensor Fusion for Remote Sensing Applications

Abstract

Remote sensing encounters different types of objects with similar spectral signatures. Multi-sensors form the solution of the problem with spectral different parts of the spectrum and the resulting information is then processed using digital signal processing techniques. Artificial neural networks provide another method for processing this information. The research describes how neural networks may be used to classify objects on the basis of their spectral response to different frequencies.