Probabilistic image sensor fusion

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

Probabilistic image sensor fusion

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

Biomedical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

39 Scopus citations

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. A Bayesian framework then provides for maximum likelihood or maximum a posteriori estimates of the true scene from the sensor images. Maximum likelihood estimates of the parameters of the image formation model involve (local) second order image statistics, and thus are related to local principal component analysis. We demonstrate the efficacy of the method on images from visible-band and infrared sensors.

Original language	English (US)
Title of host publication	Advances in Neural Information Processing Systems 11 - Proceedings of the 1998 Conference, NIPS 1998
Publisher	Neural information processing systems foundation
Pages	824-830
Number of pages	7
ISBN (Print)	0262112450, 9780262112451
State	Published - 1999
Event	12th Annual Conference on Neural Information Processing Systems, NIPS 1998 - Denver, CO, United States Duration: Nov 30 1998 → Dec 5 1998

Publication series

Name	Advances in Neural Information Processing Systems
ISSN (Print)	1049-5258

Other

Other	12th Annual Conference on Neural Information Processing Systems, NIPS 1998
Country/Territory	United States
City	Denver, CO
Period	11/30/98 → 12/5/98

ASJC Scopus subject areas

Computer Networks and Communications
Information Systems
Signal Processing

Cite this

Probabilistic image sensor fusion. / Sharma, Ravi K.; Leen, Todd K.; Pavel, Misha.
Advances in Neural Information Processing Systems 11 - Proceedings of the 1998 Conference, NIPS 1998. Neural information processing systems foundation, 1999. p. 824-830 (Advances in Neural Information Processing Systems).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Sharma, RK, Leen, TK & Pavel, M 1999, Probabilistic image sensor fusion. in Advances in Neural Information Processing Systems 11 - Proceedings of the 1998 Conference, NIPS 1998. Advances in Neural Information Processing Systems, Neural information processing systems foundation, pp. 824-830, 12th Annual Conference on Neural Information Processing Systems, NIPS 1998, Denver, CO, United States, 11/30/98.

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AB - 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. A Bayesian framework then provides for maximum likelihood or maximum a posteriori estimates of the true scene from the sensor images. Maximum likelihood estimates of the parameters of the image formation model involve (local) second order image statistics, and thus are related to local principal component analysis. We demonstrate the efficacy of the method on images from visible-band and infrared sensors.

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ER -

Probabilistic image sensor fusion

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