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The Scientific World Journal
Volume 2014, Article ID 281073, 10 pages
http://dx.doi.org/10.1155/2014/281073
Research Article

Effective Multifocus Image Fusion Based on HVS and BP Neural Network

1School of Information Technology, Jiangxi University of Finance and Economics, Nanchang 330013, China
2School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
3School of Software and Communication Engineering, Jiangxi University of Finance and Economics, Nanchang 330013, China

Received 17 July 2013; Accepted 19 December 2013; Published 6 February 2014

Academic Editors: P. Bifulco, C. Saravanan, K. Teh, and C. Zhang

Copyright © 2014 Yong Yang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [6 citations]

The following is the list of published articles that have cited the current article.

  • Jingwei Guan, and Wai-Kuen Cham, “Quality estimation based multi-focus image fusion,” 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1987–1991, . View at Publisher · View at Google Scholar
  • Yong Yang, Song Tong, Shuying Huang, and Pan Lin, “Dual-Tree Complex Wavelet Transform and Image Block Residual-Based Multi-Focus Image Fusion in Visual Sensor Networks,” Sensors, vol. 14, no. 12, pp. 22408–22430, 2014. View at Publisher · View at Google Scholar
  • Xingxing Hao, Hui Zhao, and Jing Liu, “Multifocus color image sequence fusion based on mean shift segmentation,” Applied Optics, vol. 54, no. 30, pp. 8982–8989, 2015. View at Publisher · View at Google Scholar
  • Srinivasa D. Rao, M. Seetha, Krishna M. H. M. Prasad, Srinivasa D. Rao, M. Seetha, and Krishna M. H. M. Prasad, “Quality assessment parameters for iterative image fusion using Fuzzy and Neuro Fuzzy Logic and applications,” 8Th International Conference Interdisciplinarity In Engineering, Inter-Eng 2014, vol. 19, pp. 888–894, 2015. View at Publisher · View at Google Scholar
  • M.A. Rahman, S. Liu, C.Y. Wong, S.C.F. Lin, S.C. Liu, and N.M. Kwok, “Multi-focal image fusion using degree of focus and fuzzy logic,” Digital Signal Processing, 2016. View at Publisher · View at Google Scholar
  • Ayan Seal, Debotosh Bhattacharjee, Mita Nasipuri, Dionisio Rodríguez-Esparragón, Ernestina Menasalvas, and Consuelo Gonzalo-Martin, “PET-CT image fusion using random forest and à-trous wavelet transform,” International Journal for Numerical Methods in Biomedical Engineering, pp. e2933, 2017. View at Publisher · View at Google Scholar