Open AccessFusion of color microscopic images based on bidimensional empirical mode decomposition
Author(s) -
Ying Chen,
Li Wang,
Zhibin Sun,
Yue Jiang,
Guangtao Zhai
Publication year - 2010
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.18.021757
Subject(s) - image fusion , artificial intelligence , hilbert–huang transform , computer science , luminance , computer vision , fusion , color image , wavelet transform , pattern recognition (psychology) , color difference , algorithm , wavelet , image processing , image (mathematics) , enhanced data rates for gsm evolution , linguistics , philosophy , filter (signal processing)
A novel image fusion algorithm based on bidimensional empirical mode decomposition (BEMD) applied to multi-focus color microscopic images is proposed in this paper. The fusion scheme is implemented in YIQ color model, aiming at achieving a balanced result between local feature enhancement and global tonality rendition. In the proposed algorithm, image decomposition is performed on luminance component by BEMD which can perform fully two-dimensional decomposition adaptively without using a priori basis. Upon fusion of each IMF component, the local significance principle fusion rule is used. When fusing the Residue component, the principal component analysis method is adopted. Thanks to the superior quality of BEMD in extracting salient features, the proposed algorithm can gain better fusion results not only in aspect of in-focus information extraction but also in performance of blur elimination. Experimental results demonstrate that the proposed algorithm outperforms the popular fusion algorithm based on wavelet transform. The usage of different color models for realization of the proposed algorithm is also discussed, and YIQ color model is proved to be more suitable.