A Novel Multi-Focus Images Fusion Method Based on Bidimensional Empirical Mode Decomposition

A novel images fusion method based on bidimensional empirical mode decomposition (BEMD) is proposed, aiming at solving the fusion problem of multi-focus images. BEMD is a new form of fully two-dimensional multi-scale decomposition and has superior quality in extracting salient features in multi-focu...

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Bibliographic Details
Published in2009 2nd International Congress on Image and Signal Processing pp. 1 - 4
Main Authors Ying Chen, Yuanda Jiang, Chao Wang, Di Wang, Weining Li, Guangjie Zhai
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2009
Subjects
Chaos
Data mining
Discrete wavelet transforms
Feature extraction
Focusing
Humans
Image fusion
Lenses
Multiresolution analysis
Optical microscopy
Online AccessGet full text
ISBN1424441293
9781424441297
DOI10.1109/CISP.2009.5304477

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Summary:A novel images fusion method based on bidimensional empirical mode decomposition (BEMD) is proposed, aiming at solving the fusion problem of multi-focus images. BEMD is a new form of fully two-dimensional multi-scale decomposition and has superior quality in extracting salient features in multi-focus images. This paper uses BEMD to decompose the source images into their components adaptively without using a priori basis so that the trouble in selecting some parameters such as priori basis can be leaved out. Here, Different fusion rules are applied to different image components obtained from the BEMD. Finally, all fused components are combined to get the reconstructed image. Experimental results demonstrate that the proposed method is successful in multi-focus images fusion and significantly outperforms the traditional wavelet transform-based method.
ISBN:1424441293
9781424441297
DOI:10.1109/CISP.2009.5304477