Change Detection Using Synthetic Aperture Radar Videos
This work addresses change detection for SAR video analysis, which is incremental as it adapts existing methods to a new data type.
The paper tackles change detection in SAR videos, addressing challenges like speckle noise and frame rotation, and proposes a method combining optical flow and blob detection that was tested on real and simulated SAR videos.
Many researches have been carried out for change detection using temporal SAR images. In this paper an algorithm for change detection using SAR videos has been proposed. There are various challenges related to SAR videos such as high level of speckle noise, rotation of SAR image frames of the video around a particular axis due to the circular movement of airborne vehicle, non-uniform back scattering of SAR pulses. Hence conventional change detection algorithms used for optical videos and SAR temporal images cannot be directly utilized for SAR videos. We propose an algorithm which is a combination of optical flow calculation using Lucas Kanade (LK) method and blob detection. The developed method follows a four steps approach: image filtering and enhancement, applying LK method, blob analysis and combining LK method with blob analysis. The performance of the developed approach was tested on SAR videos available on Sandia National Laboratories website and SAR videos generated by a SAR simulator.