Multifocus image fusion based on coefficient significance of redundant discrete wavelet transform
ISSN: 0143-991X
Article publication date: 14 May 2019
Issue publication date: 5 August 2019
Abstract
Purpose
This study aims to obtain the more precise decision map to fuse the source images by Coefficient significance method. In the area of multifocus image fusion, the better decision map is very important the fusion results. In the processing of distinguishing the well-focus part with blur part in an image, the edge between the parts is more difficult to be processed. Coefficient significance is very effective in generating the better decision map to fuse the multifocus images.
Design/methodology/approach
The energy of Laplacian is used in the approximation coefficients of redundant discrete wavelet transform. On the other side, the coefficient significance based on statistic property of covariance is proposed to merge the detail coefficient.
Findings
Due to the shift-variance of the redundant discrete wavelet and the effectiveness of fusion rule, the presented fusion method is superior to the region energy in harmonic cosine wavelet domain, pixel significance with the cross bilateral filter and multiscale geometry analysis method of Ripplet transform.
Originality/value
In redundant discrete wavelet domain, the coefficient significance based on statistic property of covariance is proposed to merge the detail coefficient of source images.
Keywords
Acknowledgements
Conflict of interests: The authors declare that there is no conflict of interests regarding the publication of this paper.
Citation
Liu, J., Geng, P. and Ma, H. (2019), "Multifocus image fusion based on coefficient significance of redundant discrete wavelet transform", Industrial Robot, Vol. 46 No. 3, pp. 377-383. https://doi.org/10.1108/IR-11-2018-0229
Publisher
:Emerald Publishing Limited
Copyright © 2019, Emerald Publishing Limited