CANONICAL RELATIONS OF SUBSPACES IN MULTI-SENSOR DATA ANALYSIS

Polat O. M., Ozkazanc Y.

22nd IEEE Signal Processing and Communications Applications Conference (SIU), Trabzon, Türkiye, 23 - 25 Nisan 2014, ss.1219-1222 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası:
  • Doi Numarası: 10.1109/siu.2014.6830455
  • Basıldığı Şehir: Trabzon
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.1219-1222
  • Hacettepe Üniversitesi Adresli: Evet

Özet

In multisensor data analysis, scene details can be extracted via subspace methods without any prior information on the scene In these decomposition techniques, data is projected into a new space so that the information in the data is highlighted In this study, Principal Component Analysis, Independent Component Analysis and Minumum Noise Fractions method are applied to a multi-sensor data composed of radar, visible, and infrared images. Canonical correlations between these subspaces are investigated via Canonical Correlation Analysis. This equalization subspace offers a new point of view in the realnt of multi-sensor data analysis.