Multi-focus Image Fusion by SML in the Shearlet Subbands

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

[1]  Minh N. Do,et al.  Nonsubsampled contourlet transform: construction and application in enhancement , 2005, IEEE International Conference on Image Processing 2005.

[2]  Salvador Gabarda,et al.  On the use of a joint spatial-frequency representation for the fusion of multi-focus images , 2005, Pattern Recognit. Lett..

[3]  Dong Sun Park,et al.  Medical Image Fusion via an Effective Wavelet-Based Approach , 2010, EURASIP J. Adv. Signal Process..

[4]  郭雷 Guo Lei,et al.  Image Fusion Algorithm Based on Contourlet Domain Hidden Markov Tree Models , 2010 .

[5]  Glenn R. Easley,et al.  Shearlet-Based Total Variation Diffusion for Denoising , 2009, IEEE Transactions on Image Processing.

[6]  G. Easley,et al.  Sparse directional image representations using the discrete shearlet transform , 2008 .

[7]  Qu Xiao-bo,et al.  Sum-modified-Laplacian-based Multifocus Image Fusion Method in Sharp Frequency Localized Contourlet Transform Domain , 2008 .

[8]  P. Geng,et al.  Image fusion by pulse couple neural network with shearlet , 2012 .

[9]  Gemma Piella,et al.  A general framework for multiresolution image fusion: from pixels to regions , 2003, Inf. Fusion.

[10]  D. D.-Y. Po,et al.  Directional multiscale modeling of images using the contourlet transform , 2006, IEEE Transactions on Image Processing.

[11]  Shree K. Nayar,et al.  Shape from Focus , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  George A. Stanciu,et al.  SUM-MODIFIED-LAPLACIAN FUSION METHODS EXPERIMENTED ON IMAGE STACKS OF PHOTONIC QUANTUM RING LASER DEVICES COLLECTED BY CONFOCAL SCANNING LASER MICROSCOPY , 2011 .

[13]  Vladimir Petrovic,et al.  Objective image fusion performance measure , 2000 .

[14]  Yi Chai,et al.  Multifocus image fusion scheme using focused region detection and multiresolution , 2011 .