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A New Synthetical Method of Feature Enhancement and Detection for SAR Image Targets

Shiqi Huang 1, Yiting Wang 2, and Peifeng Su 2
1. Department of Electronic Information Engineering, Xijing University, Xi’an, 710123 China
2. Xi’an Research Institute of Hi-Tech, Xi’an, 710025 China

Abstract—Target detection is important content in Synthetic Aperture Radar (SAR) image applications. There is a common target detection method, which is called the Constant False Alarm Ratio (CFAR) detector. But it must satisfy the condition under strong contrast ratio between target area and background clutter area. In fact, it is very difficult for SAR images to satisfy the condition. In order to enhance the contrast ratio and to improve the detection effect, according to the characteristics of SAR images, this paper proposed a new synthetical algorithm based on the curvelet transform and CFAR detector, called the CT-CFAR algorithm. The real SAR image data was used to test the new algorithm, and the experimental results show that the CT-CFAR algorithm can effectively improve the contrast ratio of a SAR image. Comparing with the CFAR detector, it not only can effectively detect the target, but also can obtain higher detection ratio and lower false alarm ratio.

Index Terms—synthetic aperture radar, target detection, curvelet transform, feature enhancement, constant false alarm rate

Cite: Shiqi Huang, Yiting Wang, and Peifeng Su, "A New Synthetical Method of Feature Enhancement and Detection for SAR Image Targets," Journal of Image and Graphics, Vol. 4, No. 2, pp. 73-77, December 2016. doi: 10.18178/joig.4.2.73-77