A novel algorithm for multifocus image fusion based on contourlet hidden markov tree model

Cai Xi; Zhao Wei

doi:10.1109/ICOSP.2008.4697301

A novel algorithm for multifocus image fusion based on contourlet hidden markov tree model

Cai Xi^*
, Zhao Wei

^*Corresponding author for this work

School of Electronic and Information Engineering

Beihang University

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

5 Scopus citations

Abstract

According to features of multifocus images and statistical characteristics of contourlet coefficients, a novel algorithm for multifocus image fusion based on contourlet Hidden Markov Tree model (con-HMT) is proposed. Multifocus images are used all together to train the contourlet HMT model. Then a new fusion rule for the high frequency is built. In this rule, the probability of a detailed coefficient corresponding to image edge, calculated directly from the HMT model, is chosen as the salience measure. Experimental results show that, for multifocus image fusion, the proposed algorithm provides more satisfying fusion results in terms of visual effect and objective evaluations, which proves its feasibility and validity.

Original language	English
Title of host publication	2008 9th International Conference on Signal Processing, ICSP 2008
Pages	1019-1022
Number of pages	4
DOIs	https://doi.org/10.1109/ICOSP.2008.4697301
State	Published - 2008
Event	2008 9th International Conference on Signal Processing, ICSP 2008 - Beijing, China Duration: 26 Oct 2008 → 29 Oct 2008

Publication series

Name	International Conference on Signal Processing Proceedings, ICSP

Conference

Conference	2008 9th International Conference on Signal Processing, ICSP 2008
Country/Territory	China
City	Beijing
Period	26/10/08 → 29/10/08

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10.1109/ICOSP.2008.4697301

Cite this

@inproceedings{891808f839a743edb8609cfe75d351f9,

title = "A novel algorithm for multifocus image fusion based on contourlet hidden markov tree model",

abstract = "According to features of multifocus images and statistical characteristics of contourlet coefficients, a novel algorithm for multifocus image fusion based on contourlet Hidden Markov Tree model (con-HMT) is proposed. Multifocus images are used all together to train the contourlet HMT model. Then a new fusion rule for the high frequency is built. In this rule, the probability of a detailed coefficient corresponding to image edge, calculated directly from the HMT model, is chosen as the salience measure. Experimental results show that, for multifocus image fusion, the proposed algorithm provides more satisfying fusion results in terms of visual effect and objective evaluations, which proves its feasibility and validity.",

author = "Cai Xi and Zhao Wei",

year = "2008",

doi = "10.1109/ICOSP.2008.4697301",

language = "英语",

isbn = "9781424421794",

series = "International Conference on Signal Processing Proceedings, ICSP",

pages = "1019--1022",

booktitle = "2008 9th International Conference on Signal Processing, ICSP 2008",

note = "2008 9th International Conference on Signal Processing, ICSP 2008 ; Conference date: 26-10-2008 Through 29-10-2008",

}

Xi, C & Wei, Z 2008, A novel algorithm for multifocus image fusion based on contourlet hidden markov tree model. in 2008 9th International Conference on Signal Processing, ICSP 2008., 4697301, International Conference on Signal Processing Proceedings, ICSP, pp. 1019-1022, 2008 9th International Conference on Signal Processing, ICSP 2008, Beijing, China, 26/10/08. https://doi.org/10.1109/ICOSP.2008.4697301

A novel algorithm for multifocus image fusion based on contourlet hidden markov tree model. / Xi, Cai; Wei, Zhao.
2008 9th International Conference on Signal Processing, ICSP 2008. 2008. p. 1019-1022 4697301 (International Conference on Signal Processing Proceedings, ICSP).

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

TY - GEN

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AU - Xi, Cai

AU - Wei, Zhao

PY - 2008

Y1 - 2008

N2 - According to features of multifocus images and statistical characteristics of contourlet coefficients, a novel algorithm for multifocus image fusion based on contourlet Hidden Markov Tree model (con-HMT) is proposed. Multifocus images are used all together to train the contourlet HMT model. Then a new fusion rule for the high frequency is built. In this rule, the probability of a detailed coefficient corresponding to image edge, calculated directly from the HMT model, is chosen as the salience measure. Experimental results show that, for multifocus image fusion, the proposed algorithm provides more satisfying fusion results in terms of visual effect and objective evaluations, which proves its feasibility and validity.

AB - According to features of multifocus images and statistical characteristics of contourlet coefficients, a novel algorithm for multifocus image fusion based on contourlet Hidden Markov Tree model (con-HMT) is proposed. Multifocus images are used all together to train the contourlet HMT model. Then a new fusion rule for the high frequency is built. In this rule, the probability of a detailed coefficient corresponding to image edge, calculated directly from the HMT model, is chosen as the salience measure. Experimental results show that, for multifocus image fusion, the proposed algorithm provides more satisfying fusion results in terms of visual effect and objective evaluations, which proves its feasibility and validity.

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U2 - 10.1109/ICOSP.2008.4697301

DO - 10.1109/ICOSP.2008.4697301

M3 - 会议稿件

AN - SCOPUS:67249123134

SN - 9781424421794

T3 - International Conference on Signal Processing Proceedings, ICSP

SP - 1019

EP - 1022

BT - 2008 9th International Conference on Signal Processing, ICSP 2008

T2 - 2008 9th International Conference on Signal Processing, ICSP 2008

Y2 - 26 October 2008 through 29 October 2008

ER -

A novel algorithm for multifocus image fusion based on contourlet hidden markov tree model

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