The Effect of Sub-sampling on Hyperspectral Dimension Reduction

Kozal A. Ö., Teke M., ILGIN H. A.

Advances in Intelligent Systems and Computing, cilt.210, ss.529-537, 2013 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 210
  • Basım Tarihi: 2013
  • Doi Numarası: 10.1007/978-3-319-00542-3_52
  • Dergi Adı: Advances in Intelligent Systems and Computing
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, zbMATH
  • Sayfa Sayıları: ss.529-537
  • Anahtar Kelimeler: dimension reduction, hyperspectral image classification, Hyperspectral imaging, remote sensing
  • Ankara Üniversitesi Adresli: Evet

Özet

Hyperspectral images which are captured in narrow bands in continuous manner contain very large data. This data need high processing power to classify and may contain redundant information. A variety of dimension reduction methods are used to cope with this high dimensionality. In this paper, the effect of sub-sampling hyperspectral images for dimension reduction techniques is explored and compared in classification performance and calculation time. © Springer International Publishing Switzerland 2013.