Refined aircraft segmentation in SAR images using shape prior
Xiaoqiang Zhang, Boli Xiong, Gangyao Kuang · 2017
Target segmentation is the basic work of the synthetic aperture radar (SAR) image interpretation. As for aircraft, it is difficult to accurately extract the target from the background due to its complex structure. This paper proposes a refined segmentation method for aircraft target, in which the ratio of exponentially weighted averages (ROEWA) operator is used to produce the edge map and the shape prior is utilized by the point distribution model (PDM). The Catmull-Rom (CR) spline is used to build shape samples. Combining the shape prior and the gradient vector flow (GVF) snake model, the refined segmentation of the aircraft is achieved. The experimental results based on Ku-band airborne SAR data illustrate the effective performance of the proposed method on refined segmentation for aircraft targets.