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Polarimetric Semivariogram-Based Spatial Scale Selection for PolSAR Image Segmentation with Mean-Shift Algorithm

  • Harbin Institute of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

Image segmentation has been an important procedure in object-based image analysis (OBIA), which takes image object as a processing unit. The spatial scale in image segmentation has great importance in OBIA. Due to the high heterogeneity and large dynamic range of polarimetric synthetic aperture radar (PolSAR) images, it is often difficult to choose optimal spatial scales. This letter proposes a polarimetric semivariogram-based spatial scale selection method for PolSAR image segmentation. The optimal spatial bandwidth parameter in the mean-shift algorithm is pre-estimated based on the combined polarimetric and statistical analysis of PolSAR images. By implementing a quantitative evaluation of segmentation result, the effectiveness of the proposed method in optimal spatial bandwidth selection for PolSAR image segmentation is verified. Experiments on both the EMISAR and UAVSAR L-band PolSAR data sets testify the validity of the proposed adaptive optimal bandwidth selection strategy for PolSAR images.

Original languageEnglish
Article number9102245
Pages (from-to)1239-1243
Number of pages5
JournalIEEE Geoscience and Remote Sensing Letters
Volume18
Issue number7
DOIs
StatePublished - Jul 2021

Keywords

  • High resolution
  • Mean-shift (MS) segmentation
  • Object-based image analysis (OBIA)
  • Polarimetric synthetic aperture radar (PolSAR) image
  • Spatial bandwidth

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