International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Volume XLII-3/W10
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W10, 569–574, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W10-569-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W10, 569–574, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W10-569-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  07 Feb 2020

07 Feb 2020

A LANDMARK MATCHING ALGORITHM FOR THE GEOSTATIONARY SATELLITE IMAGES BASED ON MULTI-LEVEL GRIDS

S. Y. Hou, Z. Y. Qin, L. Niu, W. G. Zhang, and W. T. Ai S. Y. Hou et al.
  • School of Surveying and Urban Spatial Information, Henan University of Urban Construction, Pingdingshan, Henan, China

Keywords: Geostationary Satellite Images, Landmark Matching, Coastline Template, Multi-level Grids, Contour Feature, Feature Matching

Abstract. The resolution of geostationary satellite image is not high and the image is covered with clouds. At present, when the extracted feature points are unstable, there are some problems, such as low matching accuracy or even matching failure. In this paper, a landmark matching algorithm is proposed to directly establish the multi-level grids for the image coastline and the coastline template. Through the similarity measure of the multi-level grids, the landmark matching is realized layer by layer. First of all, we've finished cloud detection, establishment of landmark data set, and extraction of image coastline. Then we design and implement the landmark matching algorithm based on multi-level grids. Finally, through analysis from different levels of landmarks and different proportion of cloud cover, the advantages and applicable conditions of this algorithm are given. The experimental results show that: 1) with the increase of cloud cover, the correct rate of landmark matching decreases, but the decrease is small. It shows that the matching algorithm in this paper is stable. Correct matching rate could always be stable at about 75 percent in the fourth level. 2) when the proportion of cloud cover is less than 20 percent, the higher the matching level, the higher the matching accuracy. When the cloud cover is more than 20 percent, the matching accuracy in the fourth level is the highest. This algorithm provides a stable method for the landmark matching of geostationary satellite image.