Kernel Slow Feature Analysis for Scene Change Detection

IEEE Transactions on Geoscience and Remote Sensing

Volumn 55, Issue 4, 2017, Pages 2367-2384

  Wu, Chen ^a   Zhang, Liangpei ^a   Du, Bo ^a  

^a WUHAN UNIVERSITY   (China)

Author keywords

Bayesian theory; kernel slow feature analysis (KSFA); remote sensing; rule based method; scene change detection

Indexed keywords

CLASSIFICATION (OF INFORMATION); IMAGE PROCESSING; IMAGE RECONSTRUCTION; LAND USE; REMOTE SENSING; SEMANTICS; SIGNAL DETECTION; URBAN GROWTH;

CLASSIFICATION ERRORS; HIGH RESOLUTION REMOTE SENSING IMAGES; MULTI-TEMPORAL IMAGE; POST CLASSIFICATION; SCENE CHANGE DETECTION; SCENE CLASSIFICATION; SLOW FEATURE ANALYSIS; TEMPORAL CORRELATIONS;

FEATURE EXTRACTION;

BAYESIAN ANALYSIS; DATA SET; DETECTION METHOD; IDENTIFICATION METHOD; IMAGE CLASSIFICATION; IMAGING METHOD; LAND USE; NUMERICAL METHOD; NUMERICAL MODEL; REMOTE SENSING; SATELLITE IMAGERY; URBAN DEVELOPMENT;

EID: 85009833695     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2016.2642125     Document Type: Article

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