Change Detection in Ottawa City Synthetic Aperture Radar Remote Sensing Images Based on SWT with Fuzzy C Means Clustering by Contrast Management

Abstract

The collection of techniques involved in monitoring objects on the Earth’s surface without any physical contact is called remote sensing. The change detection in remote sensing images is the process of detecting changes that take place between two SAR (Synthetic Aperture Radar) images gathered at dissimilar periods of the instance from same geographical area. The two or more SAR images obtained from the identical region at diverse time points are detected in terms of changes in accordance with the ground. Thus, the change detection mechanism is being widely employed in the field of military reconnaissance, natural calamity evaluation, and observing on marine oil spill, forest fire and urban expansion. A very often fusion s the merging of two images based on pixel level where it reduces the contrast of the fused image. In this paper Stationary Wavelet Transform (SWT) is employed for the fusion process and the fused image is segmented. Fuzzy C – Means clustering is used for segmentation and the segmented image is compared with the ground truth image. The performance of this method is measured in terms of measuring parameters accuracy, FDR, sensitivity etc.,