Approach to Moving Targets Shadow Detection for VideoSAR
ZHANG Ying① ZHU Daiyin① YU Xiang①② MAO Xinhua①
①(College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China) ②(Department of Computer Engineering, Nanjing Institute of Technology, Nanjing 211167, China)
Abstract：In the image sequence obtained by the high frame rate Video Synthetic Aperture Radar (VideoSAR) mode, the Doppler shift results in some shadows of the moving targets in their actual position, and a strong correlation exists between adjacent frames. Based on the above rationale, this paper proposes an approach to detecting moving targets’ shadow in VideoSAR imagery. First, the Scale-Invariant Feature Transform (SIFT) with RANdom SAmple Consensus (RANSAC) registration algorithm is used to compensate for the change of background of each frame, and the CattePM model is employed to suppress the speckle noise effectively. Then, in order to separate the targets and the background and generate binary images automatically, a threshold segmentation algorithm, called maximizing the Tsallis entropy, is applied. Finally, shadow detection is accomplished by the background difference with three frame difference method, and the detection results are marked on the corresponding position in the original frame. Experimental results utilizing the VideoSAR imaging fragment published by Sandia National Laboratories show that multiple moving vehicles are detected effectively, hence the validity of the approach is demonstrated.
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