中国地理科学(英文版) ›› 2002, Vol. 12 ›› Issue (3): 244-248.

• 论文 • 上一篇    下一篇

MULTI-SOURCE REMOTE SENSING IMAGE FUSION BASED ON SUPPORT VECTOR MACHINE

ZHAO Shu-he, FENG Xue-zhi, KANG Guo-ding, RAMADAN Elnazir   

  1. Department of Urban & Resources Sciences, Nanjing University, Nanjing 210093, P. R. China
  • 收稿日期:2002-06-26 出版日期:2002-09-20 发布日期:2011-12-15
  • 作者简介:ZHAO Shu-he(1971- ),male,a native of Shandong, Ph. D. His main research interests include information extraction of high spatial resolution remote sensing data, data fusion of multi-source remote sensing.
  • 基金资助:

    Under the auspices of the National Natural Science Foundation of China(No.40171015).

MULTI-SOURCE REMOTE SENSING IMAGE FUSION BASED ON SUPPORT VECTOR MACHINE

ZHAO Shu-he, FENG Xue-zhi, KANG Guo-ding, RAMADAN Elnazir   

  1. Department of Urban & Resources Sciences, Nanjing University, Nanjing 210093, P. R. China
  • Received:2002-06-26 Online:2002-09-20 Published:2011-12-15

摘要:

Remote Sensing image fusion is an effective way to use the large volume of data from multi-source images.This paper introduces a new method of remote sensing image fusion based on support vector machine (SVM), using high spatial resolution data SPIN-2 and multi-spectral remote sensing data SPOT-4. Firstly, the new method is established by building a model of remote sensing image fusion based on SVM. Then by using SPIN-2 data and SPOT-4 data, image classification fusion is tested. Finally, an evaluation of the fusion result is made in two ways. 1) From subjectivity assessment,the spatial resolution of the fused image is improved compared to the SPOT-4. And it is clearly that the texture of the fused image is distinctive. 2) From quantitative analysis, the effect of classification fusion is better. As a whole, the result shows that the accuracy of image fusion based on SVM is high and the SVM algorithm can be recommended for application in remote sensing image fusion processes.

关键词: image fusion, SVM, multi-spectral image, panchromatic image

Abstract:

Remote Sensing image fusion is an effective way to use the large volume of data from multi-source images.This paper introduces a new method of remote sensing image fusion based on support vector machine (SVM), using high spatial resolution data SPIN-2 and multi-spectral remote sensing data SPOT-4. Firstly, the new method is established by building a model of remote sensing image fusion based on SVM. Then by using SPIN-2 data and SPOT-4 data, image classification fusion is tested. Finally, an evaluation of the fusion result is made in two ways. 1) From subjectivity assessment,the spatial resolution of the fused image is improved compared to the SPOT-4. And it is clearly that the texture of the fused image is distinctive. 2) From quantitative analysis, the effect of classification fusion is better. As a whole, the result shows that the accuracy of image fusion based on SVM is high and the SVM algorithm can be recommended for application in remote sensing image fusion processes.

Key words: image fusion, SVM, multi-spectral image, panchromatic image

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