Independent-component analysis for hyperspectral remote sensing imagery classification

Optical Engineering

Volumn 45, Issue 1, 2006, Pages

  Du, Qian ^a   Kopriva, Ivica ^b   Szu, Harold ^c  

^a MISSISSIPPI STATE UNIVERSITY   (United States)

^b George Washington University   (United States)

^c OFFICE OF NAVAL RESEARCH   (United States)

Author keywords

Hyperspectral imagery; Independent component analysis; Noise adjusted principal components (NAPC) transform; Principal component analysis (PCA); Remote sensing; Unsupervised classification

Indexed keywords

DATA REDUCTION; DATA STRUCTURES; INDEPENDENT COMPONENT ANALYSIS; OBJECT RECOGNITION; PRINCIPAL COMPONENT ANALYSIS; REMOTE SENSING;

HYPERSPECTRAL IMAGERY; JOINT APPROXIMATE DIAGONALIZATION OF EIGENMATRICES; NOISE-ADJUSTED PRINCIPAL-COMPONENTS TRANSFORM; UNSUPERVISED CLASSIFICATION;

IMAGE ANALYSIS;

EID: 33748623423     PISSN: 00913286     EISSN: 15602303     Source Type: Journal    
DOI: 10.1117/1.2151172     Document Type: Article

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