Endmember Detection using Enhanced Constrained Optimization in Hyperspectral Imaging
22nd IEEE Signal Processing and Communications Applications Conference (SIU), Trabzon, Türkiye, 23 - 25 Nisan 2014, ss.1023-1026, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Cilt numarası:
- Doi Numarası: 10.1109/siu.2014.6830406
- Basıldığı Şehir: Trabzon
- Basıldığı Ülke: Türkiye
- Sayfa Sayıları: ss.1023-1026
- Hacettepe Üniversitesi Adresli: Evet
Özet
A new algorithm is presented for linear spectral mixture analysis that respects the constraints on the endmembers. The results show that it provides a more robust solution as compared to the ICE and SPICE algorithms due to the use of constrained quadratic optimization for endmember detection.