Multifocus image fusion method of Ripplet transform based on cycle spinning

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• 作者：Peng Geng ; Min Huang ; Shuaiqi Liu ; Jun Feng ; Peina Bao
• 关键词：Ripplet transform ; Cycle spinning ; Image fusion
• 刊名：Multimedia Tools and Applications
• 出版年：2016
• 出版时间：September 2016
• 年：2016
• 卷：75
• 期：17
• 页码：10583-10593
• 全文大小：953 KB
• 刊物类别：Computer Science
• 刊物主题：Multimedia Information Systems
  Computer Communication Networks
  Data Structures, Cryptology and Information Theory
  Special Purpose and Application-Based Systems
  
• 出版者：Springer Netherlands
• ISSN：1573-7721
• 卷排序：75

文摘

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.