PDF Download HTML

[1]FU Xiao,LU Heng,ZHU Qing,et al.Method of Information Extraction from High Spatial Resolution Remote Sensing Image in Earthquake-stricken Area[J].Journal of Seismological Research,2016,39(03):494-499.

Copy

Method of Information Extraction from High Spatial Resolution Remote Sensing Image in Earthquake-stricken Area

Journal of Seismological Research[ISSN 1000-0666/CN 53-1062/P] Volume: 39 Number of periods: 2016 03 Page number: 494-499 Column: Public date: 2016-07-23

Title:: Method of Information Extraction from High Spatial Resolution Remote Sensing Image in Earthquake-stricken Area

Author(s):: FU Xiao¹; LU Heng²; 3; 4; ZHU Qing¹; LI Naiwen²; 3; ZHUANG Wenhua²; 3; HE Jing⁴; (1.Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, Sichuan, China)(2.State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu 610065, Sichuan, China)(3.College of Hydraulic and Hydroelectric Engineering, Sichuan University, Chengdu 610065, Sichuan, China)(4.Key Laboratory of Geo-special Information Technology,Ministry of Land and Resources, Chengdu University of Technology, Chengdu 610059, Sichuan, China)

Keywords:: earthquake-stricken area; mean shift; information extraction; high spatial resolution remote sensing image

CLC:: P315-39

DOI:: -

Abstract:: In order to solve the problem that the spatial-temporal data is difficult to be obtained in earthquake-stricken area after the earthquake, we proposed an improved Mean Shift algorithm for information extraction. Firstly, the image was divided into texture areas and homogeneous color areas through different characteristic of variance detection on the color space. Preliminary partition on the homogeneous color area was directly achieved by Mean Shift algorithm. Meanwhile, for the texture area, a high-dimensional feature space was set up by extracting the shape, texture and color information, and the proper bandwidth was calculated according to the normalized distribution density, then the Mean Shift algorithm was applied on the feature space for model classification to reach the partition. Secondly, a cost function was set up to realize weather the adjacent area needed to be merged to smooth over the partitioned area. Finally, an information extraction matching index(EMI)which considering the area and spectrum was proposed to evaluate the extraction results. The test results for high spatial resolution remote sensing image information extraction on UAV images were conducted in Lushan and Wenchuan earthquake-stricken areas. The experimental results show that the improved Mean Shift algorithm performs better than the original ones, and provides data protection for damage information extraction of subsequent earthquake.

References:: -

Similar References:

Memo

Last Update: 1900-01-01