Study on Ballistic Missile Infrared Hyperspectral Endmember Extraction Algorithm Based on Non-negative Matrix Factorization——Performance Analysis
- Resource Type
- Conference
- Authors
- Liu, Shihua; Sheng, Wen; Jiang, Wei; Li, Guangqiang
- Source
- 2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC) Information Technology and Artificial Intelligence Conference (ITAIC), 2020 IEEE 9th Joint International. 9:183-187 Dec, 2020
- Subject
- Communication, Networking and Broadcast Technologies
Computing and Processing
Engineering Profession
Power, Energy and Industry Applications
Robotics and Control Systems
Missiles
Correlation
Libraries
Data models
Data mining
Information technology
Hyperspectral imaging
endmember extraction
ballistic missile
infrared hyperspectral
non-negative matrix factorization
algorithm perofmance analysis
- Language
- ISSN
- 2693-2865
According to the hyperspectral endmember extraction algorithm based on the non-negative matrix factorization, the performance of this method in various situation is researched. The emphases of this research are the number of the hybrid spectrums, the abundance coefficient setting methods of the hybrid spectrums and the noise in the hybrid spectrums. The simulation show that the algorithm has good performance in various situations and this method can be used in the endmember extraction of the ballistic missile hyperspectral data.