Multiscale windowed denoising and segmentation of hyperspectral images

CIMSA 2008 - IEEE Conference on Computational Intelligence for Measurement Systems and Applications Proceedings

Volumn , Issue , 2008, Pages 33-37

  Bilgin, Gökhan ^a   Ertürk, Sarp ^b   Yildirim, Tülay ^a  

^a Electronics and Telecommunication Engineering   (Turkey)

^b KOCAELI UNIVERSITY   (Turkey)

Author keywords

Adaptive resonance theory; Clustering; Denoising; Hyperspectral images; Segmentation

Indexed keywords

ARTIFICIAL INTELLIGENCE; ARTS COMPUTING; FINANCIAL DATA PROCESSING; IMAGE ENHANCEMENT; IMAGE REGISTRATION; INTELLIGENT CONTROL; LEARNING SYSTEMS;

ADAPTIVE RESONANCE THEORY; CLUSTERING; COMPUTATIONAL INTELLIGENCE; DENOISING; DENOISING APPROACH; FAST LEARNING; FUZZY-ART; HIGH-DIMENSIONAL; HYPERSPECTRAL IMAGES; INTERNATIONAL CONFERENCES; K-MEANS; MEASUREMENT SYSTEMS; MULTI SCALING; POSITIVE EFFECTS; PRINCIPAL COMPONENTS; SEGMENTATION; SEGMENTATION PROCESSING; SPATIAL INFORMATIONS; SPECTRAL SIGNATURES; VOLUME DATA;

PRINCIPAL COMPONENT ANALYSIS;

EID: 52249090450     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CIMSA.2008.4595828     Document Type: Conference Paper

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