| China Aero Geophysical Survey and Remote Sensing Center for Natural Resources | Host |
| 地质出版社 | Publish |
| Citation: |
ZHU Hongchun, HUANG Wei, LIU Haiying, ZHANG Zhongfang, WANG Bin. Research on object-oriented remote sensing change detection method based on KL divergence[J]. Remote Sensing for Natural Resources, 2017, (2): 46-52. doi: 10.6046/gtzyyg.2017.02.07
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Research on object-oriented remote sensing change detection method based on KL divergence
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Abstract
The change detection of remote sensing image has many research results from face-to-face to object-oriented operation and from the threshold to the similarity measurement;nevertheless, there are many problems such as the selection of the segmentation parameters, the determination of the change of the object and the degree of the change of the object.In view of such a situation, this paper proposes a new method based on similarity measurement to detect the change.This method has broken the performance form which has been used to detect the change of the results.Firstly, the optimal parameters of image object segmentation are calculated, and then the image patches are obtained.After that, the similarity coefficients are calculated by KL similarity calculation method, and the natural clustering features of the coefficients are calculated.The results show that the changes of the national economic development, disaster prevention and land use management decision-making are obvious, which shows the scientific nature and effectiveness of this method.-
Keywords:
- object-orient /
- image segmentation /
- change detecting /
- KL divergence /
- classification
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ZHU Hongchun, HUANG Wei, LIU Haiying, ZHANG Zhongfang, WANG Bin. Research on object-oriented remote sensing change detection method based on KL divergence[J]. Remote Sensing for Natural Resources, 2017, (2): 46-52. doi: 10.6046/gtzyyg.2017.02.07
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