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

Multi-scale segmentation of very high resolution remote sensing image based on gravitational... 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Multimedia Tools and Applications Springer Journals

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

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References (32)

Publisher
Springer Journals
Copyright
Copyright © 2017 by Springer Science+Business Media New York
Subject
Computer Science; Multimedia Information Systems; Computer Communication Networks; Data Structures, Cryptology and Information Theory; Special Purpose and Application-Based Systems
ISSN
1380-7501
eISSN
1573-7721
DOI
10.1007/s11042-017-4558-4
Publisher site
See Article on Publisher Site

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.

Journal

Multimedia Tools and Applications – Springer Journals

Published: Mar 27, 2017

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