Abstract
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.
Highlights
Polarimetric synthetic aperture radar (PolSAR) is a wellestablished multidimensional SAR technique based on acquiring earth’s surface information by means of using a pair of orthogonal polarizations for the transmitted and received electromagnetic fields [1, 2]
The level set function corresponding to these PolSAR image segmentation methods [7,8,9,10] will not be stationary when curve evolution enters into a convergence state; so it is difficult to impose a suitable termination criterion on these methods based on the value of level set function
We present several experimental results on synthetic and real PolSAR images to show the object segmentation effect of our method
Summary
Polarimetric synthetic aperture radar (PolSAR) is a wellestablished multidimensional SAR technique based on acquiring earth’s surface information by means of using a pair of orthogonal polarizations for the transmitted and received electromagnetic fields [1, 2]. In [13], a level set-based energy functional, which is a modified version of the Chan-Vese model, has been proposed for bimodal segmentation of optical image. In this paper, following on from our initial effort in [14], we develop a level set-based bimodal segmentation method for PolSAR image object segmentation using complex Gaussian/Wishart observation models. These models are demonstrated to be effective for PolSAR image segmentation in [5, 7,8,9,10].
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