Multi-frame image fusion using the expectation-maximization algorithm

Jinzhong Yang; Rick S. Blum

doi:10.1109/ICIF.2005.1591892

Multi-frame image fusion using the expectation-maximization algorithm

Jinzhong Yang, Rick S. Blum

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

10 Scopus citations

Abstract

A multi-frame image fusion scheme is proposed to fuse visual and thermal images for night vision applications. While many previous image fusion approaches perform the fusion on a frame-by-frame basis, this method considers optimum use of neighboring frames to incorporate temporal as well as sensor fusion. This fusion scheme is based on a statistical image formation model. The multiple sensor image frames are described as the true scene corrupted by additive non-Gaussian distortion. The expectation-maximization (EM) algorithm is used to estimate the parameters in the model and to produce the final fused result. The experimental results showed that the EM-based multi-frame image fusion scheme has significant advantage in terms of sensor noise reduction.

Original language	English (US)
Title of host publication	2005 7th International Conference on Information Fusion, FUSION
Publisher	IEEE Computer Society
Pages	469-474
Number of pages	6
ISBN (Print)	0780392868, 9780780392861
DOIs	https://doi.org/10.1109/ICIF.2005.1591892
State	Published - 2005
Externally published	Yes
Event	2005 8th International Conference on Information Fusion, FUSION - Philadelphia, PA, United States Duration: Jul 25 2005 → Jul 28 2005

Publication series

Name	2005 7th International Conference on Information Fusion, FUSION
Volume	1

Other

Other	2005 8th International Conference on Information Fusion, FUSION
Country/Territory	United States
City	Philadelphia, PA
Period	7/25/05 → 7/28/05

Keywords

EM algorithm
Image formation model
Multi-frame image fusion
Night vision

ASJC Scopus subject areas

General Engineering

Access to Document

10.1109/ICIF.2005.1591892

Cite this

Multi-frame image fusion using the expectation-maximization algorithm. / Yang, Jinzhong; Blum, Rick S.
2005 7th International Conference on Information Fusion, FUSION. IEEE Computer Society, 2005. p. 469-474 1591892 (2005 7th International Conference on Information Fusion, FUSION; Vol. 1).

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

Yang, J & Blum, RS 2005, Multi-frame image fusion using the expectation-maximization algorithm. in 2005 7th International Conference on Information Fusion, FUSION., 1591892, 2005 7th International Conference on Information Fusion, FUSION, vol. 1, IEEE Computer Society, pp. 469-474, 2005 8th International Conference on Information Fusion, FUSION, Philadelphia, PA, United States, 7/25/05. https://doi.org/10.1109/ICIF.2005.1591892

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AB - A multi-frame image fusion scheme is proposed to fuse visual and thermal images for night vision applications. While many previous image fusion approaches perform the fusion on a frame-by-frame basis, this method considers optimum use of neighboring frames to incorporate temporal as well as sensor fusion. This fusion scheme is based on a statistical image formation model. The multiple sensor image frames are described as the true scene corrupted by additive non-Gaussian distortion. The expectation-maximization (EM) algorithm is used to estimate the parameters in the model and to produce the final fused result. The experimental results showed that the EM-based multi-frame image fusion scheme has significant advantage in terms of sensor noise reduction.

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Multi-frame image fusion using the expectation-maximization algorithm

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

Access to Document

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