Applications of independent component analysis in endmember extraction and abundance quantification for hyperspectral imagery

IEEE Transactions on Geoscience and Remote Sensing

Volumn 44, Issue 9, 2006, Pages 2601-2616

  Wang, Jing ^a,b   Chang, Chein I ^a,b,c  

^a IEEE   (United States)

^b Baltimore County   (United States)

^c NATIONAL CHUNG HSING UNIVERSITY   (Taiwan)

Author keywords

Abundance quantification; Abundance constrained linear spectral mixture analysis (ACLSMA); Endmember extraction; FastICA; High order statistics based independent component (IC) prioritization algorithm (HOS ICPA); IC prioritization

Indexed keywords

ABUNDANCE QUANTIFICATION; ABUNDANCE-CONSTRAINED LINEAR SPECTRAL MIXTURE ANALYSIS (ACLSMA); ENDMEMBER EXTRACTION; FASTICA; HIGH-ORDER STATISTICS-BASED INDEPENDENT COMPONENT (IC) PRIORITIZATION ALGORITHM (HOS-ICPA); IC PRIORITIZATION;

ALGORITHMS; CONSTRAINT THEORY; FEATURE EXTRACTION; PRINCIPAL COMPONENT ANALYSIS; REMOTE SENSING;

IMAGE PROCESSING;

EID: 33748312145     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2006.874135     Document Type: Article

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