Computer Science ›› 2016, Vol. 43 ›› Issue (7): 67-72.doi: 10.11896/j.issn.1002-137X.2016.07.011

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Multi-focus Image Fusion Based on Twin-generation Differential Evolution and Adaptive Block Mechanism

CAO Chun-hong, ZHANG Jian-hua and LI Lin-feng   

  • Online:2018-12-01 Published:2018-12-01

Abstract: Multi-focus image fusion algorithm based on block is an important algorithm in the field of image fusion.Multi-focus image fusion algorithm based on differential evolution takes the image block size as the population of diffe-rential evolution algorithm,after many evolutions,finally getting the image block with the best fusion image effect.In order to overcome the shortcomings that the standard algorithm will lose part of the information of parent population and result in slow convergence and smaller range of global search,and when the image resolution of the corresponding blocks are same,it will change the pixels of the source images,on the basis of the multi-focus image fusion algorithm which is based on differential evolution algorithm,a new fusion algorithm was proposed by introducing the twin-generation mechanism and adaptive block mechanism.This algorithm generates two progeny populations during evolution,keeps the information of parent population to the greatest extent,expands the global search range and improves the convergence performance.When the image resolution of the corresponding blocks are the same,it cuts the image block into smaller blocks and compars their resolution,then gets a better fused image and will not change the pixel of the source images.Experimental results show that the improved algorithm can get a better fused image than the former algorithm and has better convergence performance.

Key words: Multi-focus image fusion,Differential evolution,Twin-generation,Adaptive block

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