ICIG 2015: Image and Graphics pp 263-277 | Cite as

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

Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9217)

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.

Keywords

High resolution remote sensing image Image segmentation Non-seed-based region growing Ziyuan-3 (ZY-3) Carleer evaluation method 
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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Lin Wu
    • 1
  • Yunhong Wang
    • 2
  • Jiangtao Long
    • 1
  • Zhisheng Liu
    • 1
  1. 1.Chongqing Communication CollegeChongqingChina
  2. 2.Beihang UniversityBeijingChina

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