Improved hyperspectral image classification by active learning using pre-designed mixed pixels

Pattern Recognition

Volumn 51, Issue , 2016, Pages 43-58

  Samat, Alim ^a   Li, Jun ^b   Liu, Sicong ^c   Du, Peijun ^d   Miao, Zelang ^e   Luo, Jieqiong ^d  

^a XINJIANG INSTITUTE OF ECOLOGY AND GEOGRAPHY   (China)

^b SUN YAT SEN UNIVERSITY   (China)

^c UNIVERSITY OF TRENTO   (Italy)

^d NANJING UNIVERSITY   (China)

^e HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

Author keywords

Active learning; Classification; Hyperspectral image; Low cost; Pixel purity index; Sample design; Support vector machine

Indexed keywords

CLASSIFICATION (OF INFORMATION); COMPUTATIONAL COMPLEXITY; COSTS; DIGITAL STORAGE; HYPERSPECTRAL IMAGING; IMAGE ENHANCEMENT; ITERATIVE METHODS; LEARNING SYSTEMS; PIXELS; REMOTE SENSING; SAMPLING; SPECTROSCOPY; SUPPORT VECTOR MACHINES;

ACTIVE LEARNING; CLASSIFICATION PERFORMANCE; DATA STORAGE CAPACITY; DIFFERENT RESOLUTIONS; LOW COSTS; PIXEL PURITY INDEX; REMOTE SENSING IMAGE CLASSIFICATION; SAMPLE DESIGNS;

IMAGE CLASSIFICATION;

EID: 84955719716     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2015.08.019     Document Type: Article

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