The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B2-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 1225–1232, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1225-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 1225–1232, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1225-2020

  14 Aug 2020

14 Aug 2020

SUPERPIXEL SEGMENTATION FOR POLSAR IMAGES BASED ON HEXAGON INITIALIZATION AND EDGE REFINEMENT

M. Li1, H. Zou1, Q. Ma1, J. Sun1, X. Cao1, and X. Qin2 M. Li et al.
  • 1College of Electronic Science and Technology, National University of Defense Technology, Changsha, China
  • 2School of Information and Navigation, Air Force Engineering University, Xi’an, China

Keywords: PolSAR image, Superpixel segmentation, Hexagon, Unstable pixels, Edge refinement, Initialization

Abstract. Superpixel segmentation for PolSAR images can heavily decrease the number of primitives for subsequent interpretation while reducing the impact of speckle noise. However, traditional superpixel segmentation methods for PolSAR images only focus on the boundary adherence, the significance of superpixel segmentation will be lost when the accuracy is improved at the expense of computation efficiency. To solve this problem, this paper proposes a novel superpixel segmentation algorithm for PolSAR images based on hexagon initialization and edge refinement. First, the PolSAR image is initialized as hexagonal distribution, where the complexity of searching pixels for relabelling in the local regions can be reduced by 30% theoretically. Second, all pixels in the PolSAR image are initialized as unstable pixels based on the hexagonal superpixels, which can boost the segmentation performance in the heterogeneous regions and effectively maintain all the potential edge pixels. Third, the revised Wishart distance and the spatial distance are integrated as a distance measure to relabel all unstable pixels. Finally, the postprocessing procedure based on a dissimilarity measure is applied to generate the final superpixels. Extensive experiments conducted on both the simulated and real-world PolSAR images demonstrate the superiority and effectiveness of our proposed algorithm in terms of computation efficiency and segmentation accuracy, compared to three other state-of-the-art methods.