Extraction of built-up area in plain from high resolution remote sensing images

WEN Qi1 WANG Wei1 LI Ling-ling1 MEI Li-qin2 TAN Yi-hua2

(1.National Disaster Reduction Center of China, Beijing, China 100124)
(2.College of Automation, Huazhong University of Science and Technology, Wuhan, China 430074)

【Abstract】By analyzing the textural features and local key points of the built-up area in a plain from high resolution remote sensing images, a method to extract the built-up area in the plain was proposed based on multi-kernel learning, multi-scale segmentation and multi-hypothesis voting. With the proposed method, MR8 texture characteristics and Scale Invariant Feature Transform (SIFT) algorithmwere used to extract the built-up area, and multi-characteristics were fused to implement the learning and classification to improve the robustness and stability of classifiers and to enhance the detection accuracy. Then, based on the pixel segmentation and multi-hypothesis voting, the discriminant result based on image blocks was translated into test result based on pixels to completely eliminate the block effect and to make the target area showing precise edges and shapes. The proposed method has been validated in GF-1 satellite images. The results show that the average detection precision, average recall and the average F-measure of the method have been achieved above 80%, 85%, and 80%, respectively. Moreover, its comprehensive performance is better than that of other methods. These results demonstrate the feasibility and accuracy of this method. As extraction precision of the built-up area has been to be the pixel level and the leak detection and error detection have been avoided, the built-up area images extracted are very accurate.

【Keywords】 high resolution remote sensing image; extraction of built-up area in plain; multi-hypothesis voting; multi-kernel learning; multi-scale segmentation;

【DOI】

【Funds】 National Natural Science Foundation of China (41301485) National Science and Technology Major Project of the Ministry of Science and Technology of China National High-tech R & D Program of China (863 Program)(2013AA122104)

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This Article

ISSN:1004-924X

CN: 22-1198/TH

Vol 24, No. 10, Pages 2557-2564

October 2016

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Article Outline

Abstract

  • 1 Introduction
  • 2 Detection of built-up areas in a plain from high resolution remote sensing images
  • 3 Experimental results and analysis
  • 4 Conclusion
  • References