Binary Change Guided Hyperspectral Multiclass Change Detection
Author:
Affiliation:
1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China
2. School of Computer Science, Wuhan University, Wuhan, China
Funder
National Key Research and Development Program of China
National Natural Science Foundation of China
Natural Science Foundation of Hubei Province
Fundamental Research Funds for the Central Universities
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Graphics and Computer-Aided Design,Software
Link
http://xplorestaging.ieee.org/ielx7/83/9991910/10011164.pdf?arnumber=10011164
Reference62 articles.
1. An Unsupervised Binary and Multiple Change Detection Approach for Hyperspectral Imagery Based on Spectral Unmixing
2. Unsupervised Multitemporal Spectral Unmixing for Detecting Multiple Changes in Hyperspectral Images
3. Review Article Digital change detection techniques using remotely-sensed data
4. Change Detection in Multitemporal Hyperspectral Images
5. A Review of Change Detection in Multitemporal Hyperspectral Images: Current Techniques, Applications, and Challenges
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