Toward evaluating multiscale segmentations of high spatial resolution remote sensing images

Xueliang Zhang, Pengfeng Xiao, Xuezhi Feng, Li Feng, Nan Ye

Research output: Contribution to journalArticleResearchpeer-review

30 Citations (Scopus)

Abstract

Object-based analysis of high spatial resolution remote sensing images addresses the matter of multiscale segmentation. However, existing segmentation evaluation methods mainly focus on single-scale segmentation. In this paper, we examine the issue of supervised multiscale segmentation evaluation and propose two discrepancy measures to determine the manner in which geographic objects are delineated by multiscale segmentations. A QuickBird scene in Hangzhou, China, is used to conduct the evaluation. The results reveal the effectiveness of the proposed measures, in terms of method comparison and parameter optimization, for multiscale segmentation of high spatial resolution images. Moreover, meaningful indications for selecting suitable multiple segmentation scales are presented. The proposed measures are applicable to performance evaluation and parameter optimization for multiscale segmentation algorithms.
Original languageEnglish
Pages (from-to)3694 - 3706
Number of pages13
JournalIEEE Transactions on Geoscience and Remote Sensing
Volume53
Issue number7
DOIs
Publication statusPublished - Jul 2015

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