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Yan Tao, Chen Bin, Liu Fengxian, Wang Zuocai, Guo Yufeng, Guo Siwen. Multi-focus Image Fusion Model for Micro 3D Reconstruction[J]. Journal of Computer-Aided Design & Computer Graphics, 2017, 29(9): 1613-1623.
Citation: Yan Tao, Chen Bin, Liu Fengxian, Wang Zuocai, Guo Yufeng, Guo Siwen. Multi-focus Image Fusion Model for Micro 3D Reconstruction[J]. Journal of Computer-Aided Design & Computer Graphics, 2017, 29(9): 1613-1623.

Multi-focus Image Fusion Model for Micro 3D Reconstruction

  • A new micro 3D reconstruction method based on multi-focus image fusion model was proposed which overcame the disadvantage of low efficiency in the processing of the laser scanning confocal microscopy metal samples.In the method,the micro 3D reconstruction problem was transformed into a two-dimensional image fusion problem.The whole process can be divided into three stages,including image fusion,optimal matching and iterative recovery stages.In the first phase,a novel microscopy image fusion algorithm based on m-PCNN in non-subsampled Contourlet transform(NSCT)domain was proposed,in which details of each original image can be retained to the first fusion result.In the next phase,the second fusion result and the height map were obtained by an optimal matching algorithm based on the correlation coefficient of regional image.In the last phase,an energy functional model was defined to eliminate the false information in the second fusion result.Minimization of the energy functional ensured that the second fusion result converge to the first fusion result and the height map converge to the 3D reconstruction result.The proposed method was applied to 3D reconstruction of micro-scale metal samples,and the results suggested that compared with the laser scanning confocal microscopy method,the proposed method has higher efficiency and better noise resistance.
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