Multifocus image fusion method of Ripplet transform based on cycle spinning
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The curvelet transform can represent images at both different scales and different directions. Ripplet transform, as a higher dimensional generalization of the curvelet transform, provides a new tight frame with sparse representation for images with discontinuities along C2 curves. However, the ripplet transform is lack of translation invariance, which causes the pseudo-Gibbs phenomenon on the edges of image. In this paper, the cycle spinning method is adopted to suppress the pseudo-Gibbs phenomena in the multifocus image fusion. On the other hand, a modified sum-modified-laplacian rule based on the threshold is proposed to make the decision map to select the ripplet coefficient. Several experiments are executed to compare the presented approach with other methods based on the curvelet, sharp frequency localized contourlet transform and shearlet transform. The experiments demonstrate that the presented fusion algorithm outperforms these image fusion works.
KeywordsRipplet transform Cycle spinning Image fusion
Some of the images used in this paper are available at http://www.imagefusion.org. This work was supported in part by Natural Science Foundation of China under grant 30970782, Natural Science Foundation of Hebei Province under grant 2013210094 and F2013210109, Science and Technology Research and Development of Hebei Province under grant 10213516D, the University Science Research Project of Hebei Education Department under grant 201142. The authors also thank the editors and anonymous reviewers for their valuable suggestions.
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