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Erschienen in:
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2015 | OriginalPaper | Buchkapitel

A Non-seed-based Region Growing Algorithm for High Resolution Remote Sensing Image Segmentation

verfasst von : Lin Wu, Yunhong Wang, Jiangtao Long, Zhisheng Liu

Erschienen in: Image and Graphics

Verlag: Springer International Publishing

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Abstract

One of the indispensable prerequisites for high resolution remote sensing image interpretation and processing is successful image segmentation. The algorithm presented in this paper aims for a high efficient image segmentation applicable and adaptable to high resolution remote sensing images. This is achieved by a non-seed-based region growing, which constructs neighbor pairwise pixel stack instead of depending on any seed points. The stack is constructed in increasing order of neighbor pairwise pixel spectral difference which is computed based on 4-connexity. The proposed algorithm carries out region growing according to the merging criterion (i.e. grow formula) and traversal of the stack. We apply the proposed and conventional region growing algorithms to two data sets of ZiYuan-3 (ZY-3) high resolution remote sensing images and analyze the segmentation results based on Carleer evaluation method that manifests high efficient segmentation of the proposed algorithm.

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Vorheriges Kapitel A Nonlocal Based Two-Step Method Applied to MRI Brain Image Segmentation
Nächstes Kapitel A Novel Control Point Dispersion Method for Image Registration Robust to Local Distortion
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Metadaten
Titel
A Non-seed-based Region Growing Algorithm for High Resolution Remote Sensing Image Segmentation
verfasst von
Lin Wu
Yunhong Wang
Jiangtao Long
Zhisheng Liu
Copyright-Jahr
2015
Buch
Image and Graphics

Print ISBN: 978-3-319-21977-6

Electronic ISBN: 978-3-319-21978-3

Copyright-Jahr: 2015

DOI
https://doi.org/10.1007/978-3-319-21978-3_24

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