An efficient algorithm for automatic fusion of RISAT-1 SAR data and Resourcesat-2 optical images

Abstract

Satellite Image fusion generates single hybrid image from a collection of input satellite images and helps us to extract maximum information from the remotely sensed datasets to achieve optimal spatial and spectral resolution. The critical steps of image fusion framework are co-registration of Synthetic Aperture Radar(SAR) data with corresponding optical scene, enhance the images for visual clarity and then merge the multi sensor data with a standard fusion technique. The image fusion system should perform all these steps in an automatic manner for providing ease to the user. The primary attention of this work is to examine the improvement that can be obtained by fusion of low resolution multi spectral data obtained from optical Resourcesat-2 platform (LISS-4MX/LISS-III/AWIFS Sensor having 5m/24m/56m spatial resolution) with high resolution RISAT-1 (Fine Resolution STRIPMAP (FRS-1)/Medium Resolution SCANSAR(MRS) mode data having 3m/18m spatial resolution) using SAR-Optical image fusion system discussed above. This integration of optical and SAR images from Indian Remote Sensing satellites facilitates better visual and automatic image interpretation. The Maximum Likelihood algorithm is used for classification of fused image and Resourcesat-2 multispectral data. The quality improvement of the fused product can be observed by comparing the classification accuracies of merged data with original multispectral data of the same region.