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Jianguo Yang
Donghua University

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Multi-focus Image Fusion by SML in the Shearlet Subbands Liu Jianhua; Jianguo Yang; Beizhi Li
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 1: January 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

It is now widely acknowledged that traditional wavelets are not very effective in dealing with multidimensional signals containing distributed discontinuities. Shearlet Transform is a new discrete multiscale directional representation, which combines the power of multiscale methods with a unique ability to capture the geometry of multidimensional data and is optimally efficient in representing images containing edges. In this work, coefficients with greater Sum-Modified-Laplacian are selected to combine images when high-frequency and low-frequency Shearlet subbands of source images are compared. Numerical experiments demonstrate that the method base on Shearlet Transform and Sum-Modified-Laplacian is very competitive and better than other multi-scale geometric analysis tools in multifocus image fusion both in terms of objectives performance and objective criteria. DOI : http://dx.doi.org/10.11591/telkomnika.v12i1.3365
Co-Authors Beizhi Li Liu Jianhua