Manifold coordinate representations of hyperspectral imagery: Improvements in algorithm performance and computational efficiency

Several years ago, NRL first demonstrated a computationally efficient framework for optimizing a set of intrinsic manifold coordinates for high-dimensional data such as hyperspectral imagery (HIS). Since that time, NRL has continued to improve the fidelity of the representation to describe the details of the nonlinear structure in even greater detail. In addition, working closely with CelesTech, several improvements have been made that increase the computational efficiency, accelerating processing speeds from hours to minutes.

[1]  Charles M. Bachmann,et al.  A credit assignment approach to fusing classifiers of multiseason hyperspectral imagery , 2003, IEEE Trans. Geosci. Remote. Sens..

[2]  Charles M. Bachmann Improving the performance of classifiers in high-dimensional remote sensing applications: an adaptive resampling strategy for error-prone exemplars (ARESEPE) , 2003, IEEE Trans. Geosci. Remote. Sens..

[3]  Thomas L. Ainsworth,et al.  A scalable approach to modeling nonlinear structure in hyperspectral imagery and other high-dimensional data using manifold coordinate representations , 2010, Defense + Commercial Sensing.

[4]  Thomas L. Ainsworth,et al.  Automated Estimation of Spectral Neighborhood Size in Manifold Coordinate Representations of Hyperspectral Imagery: Implications for Anomaly Finding, Bathymetry Retrieval, and Land Applications , 2008, IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium.

[5]  Thomas L. Ainsworth,et al.  Local intrinsic dimensionality of hyperspectral imagery from non-linear manifold coordinates , 2007, 2007 IEEE International Geoscience and Remote Sensing Symposium.

[6]  Thomas L. Ainsworth,et al.  Exploiting manifold geometry in hyperspectral imagery , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[7]  Thomas L. Ainsworth,et al.  Bathymetric Retrieval From Hyperspectral Imagery Using Manifold Coordinate Representations , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[8]  Thomas L. Ainsworth,et al.  Improved manifold coordinate representations of hyperspectral imagery , 2005, Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS '05..