Bulletin of Surveying and Mapping ›› 2020, Vol. 0 ›› Issue (7): 58-63.doi: 10.13474/j.cnki.11-2246.2020.0215

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Application of automatic registration method of remote sensing image in ecological environment restoration of coastal mines

XIANG Qianhe1,2, DU Juan3, CHEN Chunlei4, WANG Jianguang4   

  1. 1. China University of Geosciences(Wuhan), Wuhan 430074, China;
    2. China General Administration of Coal Geology Zhejiang Bureau of Coal Geology, Hangzhou 310021, China;
    3. Jiaxing City Planning and Design Research Institute Co., Ltd., Jiaxing 314000, China;
    4. Zhejiang Institute of Surveying and Mapping Science and technology, Hangzhou 310030, China
  • Received:2020-03-18 Revised:2020-05-19 Online:2020-07-25 Published:2020-08-01

Abstract: From the perspective of remote sensing image interpretation, this paper analyzes the role of remote sensing image interpretation in ecological restoration investigation of coastal mines, summarizes the basic methods of remote sensing interpretation of ecological restoration of coastal mines. Aiming at the problems of optical remote sensing image registration, a registration method based on shape feature of object region is proposed. A segmentation method is used to extract the structural small regions in the reference image and the image to be registered. According to the attributes of the small area and geometric shape features to match, using spatial relationships as control constraints, querying the correct small area of the same name, the center point of small region is extracted as matching control point pairs, and the parameters of affine transformation model are calculated, which effectively solves the problem of automatic registration between images. The experimental results show that the method has good experimental results and practical value, and can be used to ensure the determination of mine space location and design for the ecological restoration investigation of coastal mines.

Key words: mine ecological environment restoration, image segmentation, regional feature matching, spatial relationship constraints, automatic registration

CLC Number: