Random sampling statistical analysis for adaptive target-scale-invariant hyperspectral anomaly detection

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 6565, Issue , 2007, Pages

  Romano, João M ^a   Rosario, Dalton ^b  

^a US Army ARDEC   (United States)

^b U S ARMY RESEARCH LABORATORY   (United States)

Author keywords

Hyperspectral imagery; Parallel anomaly detection; Random sampling

Indexed keywords

BINOMIAL DISTRIBUTION; HYPERSPECTRAL IMAGERY; PARALLEL ANOMALY DETECTION; RANDOM SAMPLING;

ADAPTIVE ALGORITHMS; CLUTTER (INFORMATION THEORY); IMAGE ANALYSIS; STATISTICAL METHODS;

OBJECT RECOGNITION;

EID: 35949003645     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.719082     Document Type: Conference Paper

References (5)

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2. X. Yu, L. Hoff, I. Reed, A. Chen, L. Stotts, "Automatic target detection and recognition in multiband imagery: A unified ML detection and estimation approach," IEEE Tran. Image Processing, vol. 6, pp. 143-156, Jan. 1997.
3. H. Kwon, and N. Nasrabadi, "Kernel Orthogonal Subspace Projection for Hyperspectral Target Classification", IEEE Tran. Geoscience and Remote Sensing, vol. 43, No. 12, pp 2952-2962, Dec. 2005.
4. Anonymous
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