Polarimetric SAR Image Object Segmentation via Level Set with Stationary Global Minimum

We present a level set-based method for object segmentation in polarimetric synthetic aperture radar (PolSAR) images. In our method, a modified energy functional via active contour model is proposed based on complex Gaussian/Wishart distribution model for both single-look and multilook PolSAR images. The modified functional has two interesting properties: (1) the curve evolution does not enter into local minimum; (2) the level set function has a unique stationary convergence state. With these properties, the desired object can be segmented more accurately. Besides, the modified functional allows us to set an effective automatic termination criterion and makes the algorithm more practical. The experimental results on synthetic and real PolSAR images demonstrate the effectiveness of our method.

Abstract licence: CC BY-NC-ND

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