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Unmixing and target recognition in hyper-spectral1 Amir Z. Averbuch Valery Zheludev Michael V. Zheludev
 

Summary: Unmixing and target recognition in hyper-spectral1
images2
Amir Z. Averbuch Valery Zheludev Michael V. Zheludev
School of Computer Science
Tel Aviv University
Tel Aviv 69978, Israel
3
Abstract4
We present two new linear algorithms that perform unmixing in hyper-spectral5
images and then recognize their targets whose spectral signatures are given. The6
first algorithm is based on the ordered topology of spectral signatures. The second7
algorithm is based on a linear decomposition in each pixel's neighborhood. The sought8
after target can occupy sub- or above pixel. These algorithms combine ideas from9
algebra and probability theories as well as statistical data mining. Experimental results10
demonstrate their robustness.11
1 Introduction12
1.1 Data representation and extraction of spectral information13
We assume that an hyper-spectral signature of a sought after material is given. In many14
applications, according to (Winter, 1999), a fundamental processing task is to automatically15
identify pixels whose spectra coincide with the given spectral shape (signature). This prob-16

  

Source: Averbuch, Amir - School of Computer Science, Tel Aviv University

 

Collections: Computer Technologies and Information Sciences