1 July 2001 Bayesian sensor image fusion using local linear generative models
Author Affiliations +
Optical Engineering, 40(7), (2001). doi:10.1117/1.1384886
Abstract
We present a probabilistic method for fusion of images produced by multiple sensors. The approach is based on an image formation model in which the sensor images are noisy, locally linear functions of an underlying true scene (latent variable). A Bayesian framework then provides for maximum-likelihood or maximum a posteriori estimates of the true scene from the sensor images. Least-squares estimates of the parameters of the image formation model involve (local) second-order image statistics, and are related to local principal-component analysis. We demonstrate the efficacy of the method on images from visible-band and infrared sensors.
Ravi K. Sharma, Todd K. Leen, Misha Pavel, "Bayesian sensor image fusion using local linear generative models," Optical Engineering 40(7), (1 July 2001). http://dx.doi.org/10.1117/1.1384886
JOURNAL ARTICLE
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KEYWORDS
Image sensors

Image fusion

Sensors

Databases

Infrared imaging

Image acquisition

Statistical analysis

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