A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2010; you can also visit the original URL.
The file type is
Sensor Array and Multichannel Signal Processing Workshop Proceedings, 2002
In this ongoing work, we propose a Bayesian model that can be used to detect targets in multispectral images when the signals from the materials in the image mix linearly, the noise is Gaussian, and abundance parameters are nonnegative. By using efficient implementations of the Gibbs sampler, the expectation of any measurable functional of the abundance parameters, relative to the posterior distribution, can be computed easily. This general approach can be used to include additional constraints.doi:10.1109/sam.2002.1191009 fatcat:qauhygq4brhg7hmyq2yaty3eri