A spectral and texture-based unsupervised segmentation algorithm for human settlements land-cover extraction
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AbstractIt is crucial to evaluate human settlements to maintain human-based social development. To accurately extract human settlements land-cover information, this article focuses on the unsupervised image segmentation in high-resolution, remotely sensed imagery. J-based segmentation (JSEG) algorithm can offer good segmentation results, but it is highly dependent on image merging thresholds. In this article, a combined, unsupervised image segmentation algorithm is proposed, in which an initial segmentation result is first produced by JSEG and then the image texture is extracted for later region merging. The experiments on the high-resolution imagery show that, when compared with the results obtained by the original JSEG algorithm and eCognition, the proposed algorithm improves the segmentation accuracy. © 2012 Copyright Taylor and Francis Group, LLC.
All Author(s) ListLiu T., Lin H.
Journal nameAnnals of GIS
Volume Number18
Issue Number4
PublisherTaylor and Francis Inc.
Place of PublicationUnited Kingdom
Pages299 - 305
LanguagesEnglish-United Kingdom
Keywordshigh-resolution image, image segmentation, JSEG, texture

Last updated on 2022-16-01 at 23:33