XIA Deping, ZHANG Liang, WU Tao, et al. A multiple interference suppression algorithm based on airborne bistatic polarization radar[J]. Journal of Radars, 2022, 11(3): 399–407. doi: 10.12000/JR21212
Citation: Zhang Yue, Zou Huanxin, Shao Ningyuan, et al.. Fast superpixel segmentation algorithm for PolSAR images[J]. Journal of Radars, 2017, 6(5): 564–573. DOI: 10.12000/JR17018

Fast Superpixel Segmentation Algorithm for PolSAR Images

DOI: 10.12000/JR17018
Funds:  The National Natural Science Foundation of China (61331015, 61372163)
  • Received Date: 2017-02-28
  • Rev Recd Date: 2017-07-04
  • Available Online: 2017-07-28
  • Publish Date: 2017-10-28
  • As a pre-processing technique, superpixel segmentation algorithms should be of high computational efficiency, accurate boundary adherence and regular shape in homogeneous regions. A fast superpixel segmentation algorithm based on Iterative Edge Refinement (IER) has shown to be applicable on optical images. However, it is difficult to obtain the ideal results when IER is applied directly to PolSAR images due to the speckle noise and small or slim regions in PolSAR images. To address these problems, in this study, the unstable pixel set is initialized as all the pixels in the PolSAR image instead of the initial grid edge pixels. In the local relabeling of the unstable pixels, the fast revised Wishart distance is utilized instead of the Euclidean distance in CIELAB color space. Then, a post-processing procedure based on dissimilarity measure is empolyed to remove isolated small superpixels as well as to retain the strong point targets. Finally, extensive experiments based on a simulated image and a real-world PolSAR image from Airborne Synthetic Aperture Radar (AirSAR) are conducted, showing that the proposed algorithm, compared with three state-of-the-art methods, performs better in terms of several commonly used evaluation criteria with high computational efficiency, accurate boundary adherence, and homogeneous regularity.

     

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