Increasing hyperspectral image classification accuracy for data sets with limited training samples by sample interpolation

RAST 2009 - Proceedings of 4th International Conference on Recent Advances Space Technologies

Volumn , Issue , 2009, Pages 367-369

  Demir, Begüm ^a   Ertürk, Sarp ^a  

^a KOCAELI UNIVERSITY   (Turkey)

Author keywords

Hyperspectral images; Limited training data; Training sample interpolation

Indexed keywords

CLASSIFICATION ,; CLASSIFICATION ACCURACY; DATA SETS; HYPERSPECTRAL IMAGE CLASSIFICATION; HYPERSPECTRAL IMAGES; INTERPOLATION PROCESS; LIMITED TRAINING DATA; NUMBER OF SAMPLES; SUPPORT VECTOR; TRAINING DATA; TRAINING PATTERNS; TRAINING SAMPLE; TRAINING SAMPLE INTERPOLATION; TRAINING SETS;

ALGORITHMS; IMAGE ANALYSIS; IMAGE CLASSIFICATION; INDEPENDENT COMPONENT ANALYSIS; INTERPOLATION; SUPPORT VECTOR MACHINES;

SET THEORY;

EID: 70350431903     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/RAST.2009.5158226     Document Type: Conference Paper

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