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http://dx.doi.org/10.7780/kjrs.2018.34.6.2.6

Arctic Sea Ice Motion Measurement Using Time-Series High-Resolution Optical Satellite Images and Feature Tracking Techniques  

Hyun, Chang-Uk (Unit of Arctic Sea-Ice Prediction, Korea Polar Research Institute)
Kim, Hyun-cheol (Unit of Arctic Sea-Ice Prediction, Korea Polar Research Institute)
Publication Information
Korean Journal of Remote Sensing / v.34, no.6_2, 2018 , pp. 1215-1227 More about this Journal
Abstract
Sea ice motion is an important factor for assessing change of sea ice because the motion affects to not only regional distribution of sea ice but also new ice growth and thickness of ice. This study presents an application of multi-temporal high-resolution optical satellites images obtained from Korea Multi-Purpose Satellite-2 (KOMPSAT-2) and Korea Multi-Purpose Satellite-3 (KOMPSAT-3) to measure sea ice motion using SIFT (Scale-Invariant Feature Transform), SURF (Speeded Up Robust Features) and ORB (Oriented FAST and Rotated BRIEF) feature tracking techniques. In order to use satellite images from two different sensors, spatial and radiometric resolution were adjusted during pre-processing steps, and then the feature tracking techniques were applied to the pre-processed images. The matched features extracted from the SIFT showed even distribution across whole image, however the matched features extracted from the SURF showed condensed distribution of features around boundary between ice and ocean, and this regionally biased distribution became more prominent in the matched features extracted from the ORB. The processing time of the feature tracking was decreased in order of SIFT, SURF and ORB techniques. Although number of the matched features from the ORB was decreased as 59.8% compared with the result from the SIFT, the processing time was decreased as 8.7% compared with the result from the SIFT, therefore the ORB technique is more suitable for fast measurement of sea ice motion.
Keywords
KOMPSAT; Sea ice motion; Feature tracking; SIFT; SURF; ORB;
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