Volume XLII-2
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 501-505, 2018
https://doi.org/10.5194/isprs-archives-XLII-2-501-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 501-505, 2018
https://doi.org/10.5194/isprs-archives-XLII-2-501-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 May 2018

30 May 2018

INCORRECT MATCH DETECTION METHOD FOR ARCTIC SEA-ICE RECONSTRUCTION USING UAV IMAGES

J.-I. Kim and H.-C. Kim J.-I. Kim and H.-C. Kim
  • Unit of Arctic Sea-Ice Prediction, Korea Polar Research Institute (KOPRI), Incheon, Korea

Keywords: Unmanned Aerial Vehicle, Digital Surface Model, Image Matching, Arctic Sea-Ice

Abstract. Shapes and surface roughness, which are considered as key indicators in understanding Arctic sea-ice, can be measured from the digital surface model (DSM) of the target area. Unmanned aerial vehicle (UAV) flying at low altitudes enables theoretically accurate DSM generation. However, the characteristics of sea-ice with textureless surface and incessant motion make image matching difficult for DSM generation. In this paper, we propose a method for effectively detecting incorrect matches before correcting a sea-ice DSM derived from UAV images. The proposed method variably adjusts the size of search window to analyze the matching results of DSM generated and distinguishes incorrect matches. Experimental results showed that the sea-ice DSM produced large errors along the textureless surfaces, and that the incorrect matches could be effectively detected by the proposed method.