Unsupervised target subpixel detection in hyperspectral imagery

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 4381, Issue 1, 2001, Pages 370-379

  Chang, Chein I ^a   Du, Qian ^b   Chiang, Shao Shan ^a   Heinz, Daniel C ^a   Ginsberg, ving W ^c  

^a University of Marylandw Baltimore County   (United States)

^b TEXAS A AND M UNIVERSITY KINGSVILLE   (United States)

^c Department of Energy ^*  (United States)

Author keywords

Subpixel target detection; Unsupervised nonnegatively constrained least squares (UNCLS); Unsupervised target generation process (UTGP); Unsupervised vector quantization (UVQ)

Indexed keywords

IMAGE ANALYSIS; LEARNING ALGORITHMS; LEAST SQUARES APPROXIMATIONS; VECTOR QUANTIZATION;

HYPERSPECTRAL IMAGERY (HSI); UNSUPERVISED TARGET SUBPIXEL DETECTION;

IMAGE SENSORS;

EID: 0035158127     PISSN: 0277786X     EISSN: None     Source Type: Journal    
DOI: 10.1117/12.437027     Document Type: Article

References (9)

1. Subpixel spectral detection for remotely sensed images
2. An algorithm for vector quantizer design
3. A new initialization technique for generalization Lloyd iteration
4. An unsupervised vector quantization-based target signature subspace projection approach to classification and detection in unknown background
5. A generalized orthogonal subspace projection approach to unsupervised multispectral image classification
6. Hyperspectral image classification and dimensionality reduction: An orthogonal subspace projection