Computer Science

Computer Science ›› 2019, Vol. 46 ›› Issue (9): 254-258.doi: 10.11896/j.issn.1002-137X.2019.09.038

• Graphics,Image & Pattern Recognition • Previous Articles     Next Articles

Multi-focus Image Fusion Based on Latent Sparse Representation and Neighborhood Information

ZHANG Bing1,2, XIE Cong-hua2, LIU Zhe3   

  1. (School of Computer Science and Technology,Soochow University,Suzhou,Jiangsu 215006,China)1;
    (School of Computer Science and Engineering,Changshu Institute of Technology,Suzhou,Jiangsu 215500,China)2;
    (School of Computer Science and Communication Engineering,Jiangsu University,Zhenjiang,Jiangsu 212013,China)3
  • Received:2018-07-03 Online:2019-09-15 Published:2019-09-02

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Abstract: This paper presented a novel fusion method based on latent sparse representation model for edge blurring and ghost in multi-focus image fusion.Firstly,it decomposes the image into public features,unique features and detail information by using latent sparse representation.Secondly,it combines unique features and detail information to determine the focused and defocused regions.Finally,it uses source information fused multi-focus images based on context information.A large number of experimental results show that the proposed method can effectively fuse multi-focus images.Compared with the most advanced methods,the images processed by this algorithm retain more information of the source image.At the same time,the ghost of the unregistered images is reduced,and the fusion effect of the image is greatly improved.

Key words: Multi-focus image fusion, Neighborhood information, Sparse representation, Unregistered images

CLC Number: 

  • TP391
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