Change detection and tracking using synthetic aperture radar videos

Abstract

In this paper, a change detection technique which can be utilized in identifying important changes in SAR videos has been proposed. Even though most researches have done on change detection in multi temporal SAR images, implementing a methodology to identify changes in SAR videos in a near real time manner has unique challenges such as the inherent speckle noise which will increase the false positive rate of the detection, rotation of the reconstructed SAR video frames due to the movement of the airborne vehicle, dynamic background and the overlapping of the area in consecutive video frames, non-uniform backscattering of SAR pulses and shadowy modelling of objects in video frames which doesn't provide much information about the appearance model of the objects. We propose an algorithm based on combination of optical flow calculation using Lucas Kanade method(LK method) and blob detection to detect the changes, and we feed the detected changes along with optical flow calculations to a centroid tracking algorithm to track the detected changes throughout the video.