• Opto-Electronic Engineering
  • Vol. 35, Issue 12, 63 (2008)
MENG Yu1、2、*, ZHAO Zhong-ming1, LIU Xing-chun3, and TANG Quan1、2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
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    DOI: Cite this Article
    MENG Yu, ZHAO Zhong-ming, LIU Xing-chun, TANG Quan. Automatic Extraction of Changed Region Based on Maximal Variance Between-class[J]. Opto-Electronic Engineering, 2008, 35(12): 63 Copy Citation Text show less

    Abstract

    Extracting changed areas from different images was an important problem in the field of remote sensing image change detection.To solve this problem,a method based on maximal variance between-class criteria and C-means algorithm was proposed.Changed area extraction was converted into a typical problem of two-category classification and could be solved by employing threshold strategy.The C-means algorithm is used to classify an image into two classes and obtained its best threshold when the variance between-class is maximal.The experimental results show that the method can automatically determine the best image change detection threshold and extract the changed areas quickly and accurately.
    MENG Yu, ZHAO Zhong-ming, LIU Xing-chun, TANG Quan. Automatic Extraction of Changed Region Based on Maximal Variance Between-class[J]. Opto-Electronic Engineering, 2008, 35(12): 63
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