Multi-scale segmentation of very high resolution remote sensing image based on gravitational field and optimized region merging

Ai Zhu Zhang, Gen Yun Sun, Si Han Liu, Zhen Jie Wang, Peng Wang, Jingsheng Ma

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

This paper proposes a multi-scale segmentation approach for high resolution remote sensing image (HRRSI) based on the gravitational field and region merging. In this approach, the HRRSI is firstly transformed into a gravitational field by incorporating the spatial and spectral information. Based on which, the attraction among neighboring pixels will cause travelling of each pixel. During the travelling, pixels with similar spectral information which are at the nearby location get grouped, which define an initial segmentation for the HRRSI which is often over-segmented in places. Then, an improved graph based region merging method is adopted to merge the over-segmented regions which yield the multi-scale segmentation results. To evaluate the proposed approach, we conduct extensive experiments on three HRRSIs from different sensors and the obtained results are compared with those of eCognition’s multi-resolution segmentation method. The experimental results show that the proposed approach reduces much more over-segmentation problem and produces more accurate image segmentation.

Original languageEnglish
Pages (from-to)15105-15122
Number of pages18
JournalMultimedia Tools and Applications
Volume76
Issue number13
Early online date27 Mar 2017
DOIs
Publication statusPublished - Jul 2017

Keywords

  • Gravitational field
  • High resolution
  • Image segmentation
  • Region merging
  • Remote sensing

ASJC Scopus subject areas

  • Software
  • Media Technology
  • Hardware and Architecture
  • Computer Networks and Communications

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