Vehicle target detection in SAR image based on complex data statistics and superpixel characteristics

Tao Tang; Jing Peng; Deliang Xiang

doi:10.1117/12.2574442

20 September 2020 Vehicle target detection in SAR image based on complex data statistics and superpixel characteristics

Tao Tang, Jing Peng, Deliang Xiang

Proceedings Volume 11533, Image and Signal Processing for Remote Sensing XXVI; 115331Q (2020) https://doi.org/10.1117/12.2574442
Event: SPIE Remote Sensing, 2020, Online Only

Conference Poster

Abstract

In this paper, a new kind of feature(AT feature) to measure the possibility of artificial target in SAR image was proposed based on the difference between real part and imaginary part of complex data of single-channel SAR imagery. Under the guidance of this feature, a superpixel-level CFAR detection method (AS-CFAR) was proposed for vehicle targets. The proposed method consists of three steps. Firstly superpixel segmentation algorithm was used to presegment SAR images. Then AT feature was calculated to find out the potential target superpixel and background superpixel using SAR complex data. Finally, CFAR detection was carried out only for the superpixels of potential targets, and the selection of background area was also conducted under AT features, which maximally ensured the uniformity of background area. Experiments on miniSAR data verified that the proposed method could detect more target pixels in less time than other CFAR detectors.

Citation Download Citation

Tao Tang, Jing Peng, and Deliang Xiang "Vehicle target detection in SAR image based on complex data statistics and superpixel characteristics", Proc. SPIE 11533, Image and Signal Processing for Remote Sensing XXVI, 115331Q (20 September 2020); https://doi.org/10.1117/12.2574442

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