Bayesian sensor image fusion using local linear generative models

Ravi K. Sharma; Todd K. Leen; Misha Pavel

doi:10.1117/1.1384886

1 July 2001 Bayesian sensor image fusion using local linear generative models

Ravi K. Sharma, Todd K. Leen, Misha Pavel

Optical Engineering, Vol. 40, Issue 7, (July 2001). https://doi.org/10.1117/1.1384886

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.

©(2001) Society of Photo-Optical Instrumentation Engineers (SPIE)

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Ravi K. Sharma, Todd K. Leen, and Misha Pavel "Bayesian sensor image fusion using local linear generative models," Optical Engineering 40(7), (1 July 2001). https://doi.org/10.1117/1.1384886

Published: 1 July 2001

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