A new wavelet-domain HMTseg algorithm for remotely sensed image segmentation

  • Authors:

  • Qiang Sun;Biao Hou;Li-cheng Jiao

  • Affiliations:

  • Institute of Intelligent Information Processing, Xidian University, Xi'an, China;Institute of Intelligent Information Processing, Xidian University, Xi'an, China;Institute of Intelligent Information Processing, Xidian University, Xi'an, China

  • Venue:
  • ICIAP'05 Proceedings of the 13th international conference on Image Analysis and Processing
  • Year:
  • 2005

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Abstract

A new wavelet-domain HMTseg method is proposed, which fuses the segmentation results at coarse and fine scales with a new and feasible context model together with one preprocessing of raw segmentations at different scales. Compared to the original HMTseg method, the new method not only lays emphasis on the performance from coarse-scale segmentation, preserves the main outlines of the homogeneous regions in an image, and thus achieves good region consistency of segmentation, but also take into account the information from fine-scale segmentation, thus improves the accuracy of boundary localization of segmentation and enables the discrimination of small targets in an image, which is desirable for interpretation of remotely sensed images. Experiments on remotely sensed images, including aerial photos and SAR images, demonstrate that the proposed method can effectively take into consideration both the region consistency and the accuracy of boundary localization of segmentation performance, and give better segmentation results.