Chaos theory-based data-mining technique for image endmember extraction: Laypunov index and correlation dimension (L and D)

IEEE Transactions on Geoscience and Remote Sensing

Volumn 52, Issue 4, 2014, Pages 1935-1947

  Zhang, Anbing ^a   Xie, Yichun ^b  

^a HEBEI UNIVERSITY OF ENGINEERING   (China)

^b EASTERN MICHIGAN UNIVERSITY   (United States)

Author keywords

Chaos theory; Correlation dimension; Dessert steppe; Endmember extraction (EE); Grassland classification; Lyapunov index

Indexed keywords

CHAOS THEORY; EXTRACTION; IMAGE CLASSIFICATION; IMPORTANCE SAMPLING; SUPPORT VECTOR MACHINES;

CORRELATION DIMENSIONS; DESSERT STEPPE; ENDMEMBER EXTRACTION; GRASSLAND CLASSIFICATIONS; LYAPUNOV INDEX;

IMAGE PROCESSING;

ACCURACY ASSESSMENT; CHAOS THEORY; DATA MINING; DATA SET; GRASSLAND; IMAGE ANALYSIS; PIXEL; STEPPE; VEGETATION CLASSIFICATION; VEGETATION MAPPING;

CHINA; NEI MONGGOL; WULATE ZHONGQI;

HYPERION;

EID: 84892444054     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2013.2256790     Document Type: Article

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