A multi-scale region growing segmentation for high resolution remotely sensed images

Li Yu Chang, Chi Farn Chen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

For remotely sensed images, region growing segmentation is a widely-used technique for object extraction and identification. However, the main drawback of region growing segmentation is the threshold setting for stopping the growth of a region. Improper threshold setting not only causes over-segmentation or under-segmentation, but also cannot create needed object regions for various targets. In order to overcome these drawbacks, a multi-scale region growing segmentation method, based on the maximization of the change of edge density, is proposed. Experiments, including different kinds of high resolution remotely sensed images are used to test the performance of the proposed scheme. The experimental results show that the proposed scheme can both remove the limitation of threshold setting and generate relatively reasonable segmentation output for different types of objects.

Original languageEnglish
Title of host publication28th Asian Conference on Remote Sensing 2007, ACRS 2007
Pages2111-2116
Number of pages6
StatePublished - 2007
Event28th Asian Conference on Remote Sensing 2007, ACRS 2007 - Kuala Lumpur, Malaysia
Duration: 12 Nov 200716 Nov 2007

Publication series

Name28th Asian Conference on Remote Sensing 2007, ACRS 2007
Volume3

Conference

Conference28th Asian Conference on Remote Sensing 2007, ACRS 2007
Country/TerritoryMalaysia
CityKuala Lumpur
Period12/11/0716/11/07

Keywords

  • Edge density
  • High resolution images
  • Image segmentation

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