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Urban Change Detection Between Heterogeneous Images Using the Edge Information
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 Title & Authors
Urban Change Detection Between Heterogeneous Images Using the Edge Information
Jae Hong, Oh; Chang No, Lee;
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 Abstract
Change detection using the heterogeneous data such as aerial images, aerial LiDAR (Light Detection And Ranging), and satellite images needs to be developed to efficiently monitor the complicating land use change. We approached this problem not relying on the intensity value of the geospatial image, but by using RECC(Relative Edge Cross Correlation) which is based on the edge information over the urban and suburban area. The experiment was carried out for the aerial LiDAR data with high-resolution Kompsat-2 and −3 images. We derived the optimal window size and threshold value for RECC-based change detection, and then we observed the overall change detection accuracy of 80% by comparing the results to the manually acquired reference data.
 Keywords
Change Detection;Edge Information;RECC;LiDAR;High-resolution Satellite Images;
 Language
Korean
 Cited by
1.
Discriminative Feature Learning for Unsupervised Change Detection in Heterogeneous Images Based on a Coupled Neural Network, IEEE Transactions on Geoscience and Remote Sensing, 2017, 55, 12, 7066  crossref(new windwow)
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