Multi-Focus Image Fusion Based on NSCT and NSST

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• 作者：Altan-Ulzii Moonon (1)
  Jianwen Hu (2)
  
  1. College of Electrical and Information Engineering ; Hunan University ; Changsha ; 410082 ; People鈥檚 Republic of China
  2. College of Electrical and Information Engineering ; Changsha University of Science and Technology ; Changsha ; 410114 ; People鈥檚 Republic of China
  
• 关键词：Multi ; focus image fusion ; Nonsubsampled contourlet transform ; Nonsubsampled shearlet transform ; Low frequency coefficient ; High frequency coefficient
• 刊名：Sensing and Imaging: An International Journal
• 出版年：2015
• 出版时间：November 2015
• 年：2015
• 卷：16
• 期：1
• 全文大小：1,043 KB
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  12. Qu, XB, Yan, JW, Xiao, HZ, Zhu, ZQ (2009) Image fusion algorithm based on spatial frequency-motivated pulse coupled neural networks in nonsubsampled contourlet transform domain. Acta Automatica Sinica 34: pp. 1508-1514 CrossRef
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• 刊物类别：Engineering
• 刊物主题：Electronic and Computer Engineering
  Microwaves, RF and Optical Engineering
  Imaging and Radiology
  
• 出版者：Springer New York
• ISSN：1557-2072

文摘

In this paper, a multi-focus image fusion algorithm based on the nonsubsampled contourlet transform (NSCT) and the nonsubsampled shearlet transform (NSST) is proposed. The source images are first decomposed by the NSCT and NSST into low frequency coefficients and high frequency coefficients. Then, the average method is used to fuse low frequency coefficient of the NSCT. To obtain more accurate salience measurement, the high frequency coefficients of the NSST and NSCT are combined to measure salience. The high frequency coefficients of the NSCT with larger salience are selected as fused high frequency coefficients. Finally, the fused image is reconstructed by the inverse NSCT. We adopt three metrics (Q AB/F , Q e and Q w ) to evaluate the quality of fused images. The experimental results demonstrate that the proposed method outperforms other methods. It retains highly detailed edges and contours.