Hyperspectral Subspace Identification

Subspace system identification

We give a general overview of the state-of-the-art in subspace system identification methods. We have restricted ourselves to the most important ideas and developments since the methods appeared in the late eighties. First, the basis of linear subspace identification are summarized. Different algorithms one finds in literature (Such as N4SID, MOESP, CVA) are discussed and put into a unifyin...

Adaptive Subspace Target Detection in Hyperspectral Imagery

* Corresponding author. Abstract –Adaptive subspace detectors are widely used for low probability and anomaly detection. The complex remote sensing conditions in which hyperspectral imagery is obtained make the detector performance evaluation a non-trivial task. Many of the detector design parameters can only be studied empirically for their effects on detection performance. In this paper, hype...

Spatial Subspace Clustering for Hyperspectral Data Segmentation

We propose a novel method called spatial subspace clustering (SpatSC) for 1D hyperspectral data segmentation problem, e.g. hyperspectral data taken from a drill hole. Addressing this problem has several practical uses such as improving interpretability of the data, and especially a better understanding of the mineralogy. Spatial subspace clustering is a combination of subspace learning and the ...

Hyperspectral Subspace Identification and Endmember Extraction by Integration of Spatial-Spectral Information

DISCLAIMER This document describes work undertaken as part of a programme of study at the Faculty of Geo-Information Science and Earth Observation of the University of Twente. All views and opinions expressed therein remain the sole responsibility of the author, and do not necessarily represent those of the Faculty. i ABSTRACT This research work concentrates on understanding the concepts of hyp...

Subspace Identification Methods