@inproceedings{13eec862563e40daa107c7a370093c22,
title = "Adaptive feature-specific spectral imaging",
abstract = "We present an architecture for rapid spectral classification in spectral imaging applications. By making use of knowledge gained in prior measurements, our spectral imaging system is able to design adaptive feature-specific measurement kernels that selectively attend to the portions of a spectrum that contain useful classification information. With measurement kernels designed using a probabilistically-weighted version of principal component analysis, simulations predict an orders-of-magnitude reduction in classification error rates. We report on our latest simulation results, as well as an experimental prototype currently under construction.",
keywords = "Adaptive optics, Computational sensing, Spectral imaging",
author = "Jansen, {P. A.} and Dunlop, {M. J.} and Golish, {D. R.} and Gehm, {M. E.}",
year = "2012",
doi = "10.1117/12.918856",
language = "English (US)",
isbn = "9780819490438",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
booktitle = "Compressive Sensing",
note = "Compressive Sensing ; Conference date: 26-04-2012 Through 27-04-2012",
}