A novel approach for image fusion based on Markov Random Fields

Min Xu; Hao Chen; Pramod K. Varshney

doi:10.1109/CISS.2008.4558549

A novel approach for image fusion based on Markov Random Fields

Min Xu, Hao Chen, Pramod K. Varshney

Department of Electrical Engineering & Computer Science

Research output: Chapter in Book/Entry/Poem › Conference contribution

4 Scopus citations

Abstract

Markov Random Field (MRF) model is a powerful tool to model image characteristics accurately and has been successfully applied to a large number of image processing applications. This paper investigates the problem of image fusion based on MRF models. A fusion algorithm under the maximum a posteriori (MAP) criterion is developed under this model. Experimental results are provided to demonstrate the improvement of fusion performance by our algorithm.

Original language	English (US)
Title of host publication	CISS 2008, The 42nd Annual Conference on Information Sciences and Systems
Pages	344-349
Number of pages	6
DOIs	https://doi.org/10.1109/CISS.2008.4558549
State	Published - 2008
Event	CISS 2008, 42nd Annual Conference on Information Sciences and Systems - Princeton, NJ, United States Duration: Mar 19 2008 → Mar 21 2008

Publication series

Name	CISS 2008, The 42nd Annual Conference on Information Sciences and Systems

Other

Other	CISS 2008, 42nd Annual Conference on Information Sciences and Systems
Country/Territory	United States
City	Princeton, NJ
Period	3/19/08 → 3/21/08

ASJC Scopus subject areas

Computer Science Applications
Information Systems
Control and Systems Engineering

Access to Document

10.1109/CISS.2008.4558549

Cite this

Xu, M, Chen, H & Varshney, PK 2008, A novel approach for image fusion based on Markov Random Fields. in CISS 2008, The 42nd Annual Conference on Information Sciences and Systems., 4558549, CISS 2008, The 42nd Annual Conference on Information Sciences and Systems, pp. 344-349, CISS 2008, 42nd Annual Conference on Information Sciences and Systems, Princeton, NJ, United States, 3/19/08. https://doi.org/10.1109/CISS.2008.4558549

@inproceedings{4e9a0a3f5ac34d8e87fc023e3713fd99,

title = "A novel approach for image fusion based on Markov Random Fields",

abstract = "Markov Random Field (MRF) model is a powerful tool to model image characteristics accurately and has been successfully applied to a large number of image processing applications. This paper investigates the problem of image fusion based on MRF models. A fusion algorithm under the maximum a posteriori (MAP) criterion is developed under this model. Experimental results are provided to demonstrate the improvement of fusion performance by our algorithm.",

author = "Min Xu and Hao Chen and Varshney, {Pramod K.}",

year = "2008",

doi = "10.1109/CISS.2008.4558549",

language = "English (US)",

isbn = "9781424422470",

series = "CISS 2008, The 42nd Annual Conference on Information Sciences and Systems",

pages = "344--349",

booktitle = "CISS 2008, The 42nd Annual Conference on Information Sciences and Systems",

note = "CISS 2008, 42nd Annual Conference on Information Sciences and Systems ; Conference date: 19-03-2008 Through 21-03-2008",

}

TY - GEN

T1 - A novel approach for image fusion based on Markov Random Fields

AU - Xu, Min

AU - Chen, Hao

AU - Varshney, Pramod K.

PY - 2008

Y1 - 2008

N2 - Markov Random Field (MRF) model is a powerful tool to model image characteristics accurately and has been successfully applied to a large number of image processing applications. This paper investigates the problem of image fusion based on MRF models. A fusion algorithm under the maximum a posteriori (MAP) criterion is developed under this model. Experimental results are provided to demonstrate the improvement of fusion performance by our algorithm.

AB - Markov Random Field (MRF) model is a powerful tool to model image characteristics accurately and has been successfully applied to a large number of image processing applications. This paper investigates the problem of image fusion based on MRF models. A fusion algorithm under the maximum a posteriori (MAP) criterion is developed under this model. Experimental results are provided to demonstrate the improvement of fusion performance by our algorithm.

UR - http://www.scopus.com/inward/record.url?scp=51849148686&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=51849148686&partnerID=8YFLogxK

U2 - 10.1109/CISS.2008.4558549

DO - 10.1109/CISS.2008.4558549

M3 - Conference contribution

AN - SCOPUS:51849148686

SN - 9781424422470

T3 - CISS 2008, The 42nd Annual Conference on Information Sciences and Systems

SP - 344

EP - 349

BT - CISS 2008, The 42nd Annual Conference on Information Sciences and Systems

T2 - CISS 2008, 42nd Annual Conference on Information Sciences and Systems

Y2 - 19 March 2008 through 21 March 2008

ER -

A novel approach for image fusion based on Markov Random Fields

Abstract

Publication series

Other

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this