Detection of flooded areas from multitemporal SAR images

Multi temporal synthetic aperture radar images are available, precise calibration and perfect spatial register are required to get a useful image for displaying changes that contain occurred. SAR calibration is a extremely complex and sensitive problem; a few errors may persist after calibration that interferes with subsequent steps in the data fusion and visualization process. Because of the non-Gaussian model of radar backscattering, traditional image pre processing procedures cannot be used here. To solve this problem “cross-calibration/normalization,” method can be used. In image enhancement and the numerical comparison of many image takes together with data fusion and visualization processes. The proposed processing which contain filtering, histogram truncation, and equalization steps and region growing and merging algorithm applied in an adaptive way to the images. RGB composition is used to combining an pre & post flood image or identify an flooded areas.