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文章基本信息

  • 标题:Multi-Focus Image Fusion Based on Sparse Decomposition
  • 本地全文:下载
  • 作者:Yongxin Zhang
  • 期刊名称:International Journal of Signal Processing, Image Processing and Pattern Recognition
  • 印刷版ISSN:2005-4254
  • 出版年度:2015
  • 卷号:8
  • 期号:2
  • 页码:157-164
  • DOI:10.14257/ijsip.2015.8.2.16
  • 出版社:SERSC
  • 摘要:In order to effectively improve fusion quality, a novel multi-focus image fusion approach with sparse decomposition is proposed. The source images are decomposed into principal and sparse components by robust principal component analysis (RPCA) decomposition. A sliding window technique is applied to inhibiting blocking artifacts. The focused pixels of the source images are detected by using the salient features within the sliding window and integrated to construct the final fused image. Experimental results show that the proposed scheme can significantly inhibit the blocking artifacts compared to the other existing fusion methods in terms of some visual and objective evaluations
  • 关键词:image fusion; robust principal component analysis; sliding window; sparse ; feature
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