A new change-detection method in high-resolution remote sensing images based on a conditional random field model
Author:
Affiliation:
1. The School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, China
Funder
National Natural Science Foundation of China
Publisher
Informa UK Limited
Subject
General Earth and Planetary Sciences
Link
https://www.tandfonline.com/doi/pdf/10.1080/01431161.2016.1148284
Reference29 articles.
1. 10.35 μm: atmospheric window on the GOES-R Advanced Baseline Imager with less moisture attenuation
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3. Analysis and Adaptive Estimation of the Registration Noise Distribution in Multitemporal VHR Images
4. Automatic analysis of the difference image for unsupervised change detection
5. Automatic change detection in high-resolution remote-sensing images by means of level set evolution and support vector machine classification
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