Comparative analysis of hyperspectral dimension reduction methods Hiperspektral boyut indirgeme yöntemlerinin karşilaş tirilmali analizi

Kozal A. Ö., Teke M., ILGIN H. A.

2013 21st Signal Processing and Communications Applications Conference, SIU 2013, Haspolat, Türkiye, 24 - 26 Nisan 2013 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/siu.2013.6531487
  • Basıldığı Şehir: Haspolat
  • Basıldığı Ülke: Türkiye
  • Anahtar Kelimeler: Dimension reduction, Hyperspectral image classification, Hyperspectral imaging, Remote sensing
  • Ankara Üniversitesi Adresli: Evet

Özet

Hyperspectral sensors generate images in narrow bands in continuous manner with hundreds of spectral bands. The data with large number of bands require more processing power to classify. To decrease the redundancy in hyperspectral images and increase classifying efficiency with less number of bands, dimension reduction techniques are applied. In this paper, linear and non-linear dimension reduction methods are compared in classification performance and calculation time. © 2013 IEEE.