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Abstract and Applied Analysis
Volume 2013, Article ID 585310, 10 pages
http://dx.doi.org/10.1155/2013/585310
Research Article

Fractional-Order Total Variation Image Restoration Based on Primal-Dual Algorithm

1College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110006, China
2MESA Lab, University of California, Merced, 5200 North Lake Road, Merced, CA 95343, USA

Received 7 August 2013; Accepted 27 September 2013

Academic Editor: Dumitru Baleanu

Copyright © 2013 Dali Chen 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 [20 citations]

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

  • Pushpendra Kumar, Sanjeev Kumar, and Balasubramanian Raman, “A fractional order variational model for tracking the motion of objects in the applications of video surveillance,” 2016 Eighth International Conference on Advanced Computational Intelligence (ICACI), pp. 117–123, . View at Publisher · View at Google Scholar
  • Asmat Ullah, Wen Chen, and Mushtaq A. Khan, “Fracto-integer order total variation based multiplicative noise removal model,” 2015 5th International Conference on Information Science and Technology (ICIST), pp. 160–165, . View at Publisher · View at Google Scholar
  • Pushpendra Kumar, Sanjeev Kumar, and R. Balasubramanian, “A fractional order total variation model for the estimation of optical flow,” 2015 Fifth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG), pp. 1–4, . View at Publisher · View at Google Scholar
  • Dong Chen, Sandeep Kalra, David Irwin, Prashant Shenoy, and Jeannie Albrecht, “Preventing Occupancy Detection From Smart Meters,” Ieee Transactions On Smart Grid, vol. 6, no. 5, pp. 2426–2434, 2015. View at Publisher · View at Google Scholar
  • Mona Alimohammadi, Joseph M. Sherwood, Morad Karimpour, Obiekezie Agu, Stavroula Balabani, and Vanessa Diaz-Zuccarini, “Aortic dissection simulation models for clinical support: fluid-structure interaction vs. rigid wall models,” Biomedical Engineering Online, vol. 14, 2015. View at Publisher · View at Google Scholar
  • Justin Drager, Edward J. Harvey, and Jake Barralet, “Hypoxia signalling manipulation for bone regeneration,” Expert Reviews In Molecular Medicine, vol. 17, 2015. View at Publisher · View at Google Scholar
  • Dali Chen, YangQuan Chen, and Dingyu Xue, “Fractional-order total variation image denoising based on proximity algorithm,” Applied Mathematics and Computation, 2015. View at Publisher · View at Google Scholar
  • Jianping Zhang, and Ke Chen, “A Total Fractional-Order Variation Model for Image Restoration with Nonhomogeneous Boundary Conditions and Its Numerical Solution,” SIAM Journal on Imaging Sciences, vol. 8, no. 4, pp. 2487–2518, 2015. View at Publisher · View at Google Scholar
  • Fusen Pan, Jiaqing Wang, Zhenzhong Yang, Lin Gu, and Yan Yu, “MoS2-graphene nanosheet-CNT hybrids with excellent electrochemical performances for lithium-ion batteries,” Rsc Advances, vol. 5, no. 95, pp. 77518–77526, 2015. View at Publisher · View at Google Scholar
  • Asmat Ullah, Wen Chen, and Mushtaq Ahmad Khan, “A new variational approach for restoring images with multiplicative noise,” Computers & Mathematics With Applications, vol. 71, no. 10, pp. 2034–2050, 2016. View at Publisher · View at Google Scholar
  • Pushpendra Kumar, and Balasubramanian Raman, “Motion Estimation from Image Sequences: A Fractional Order Total Variation Model,” Proceedings of International Conference on Computer Vision and Image Processing, vol. 460, pp. 297–307, 2016. View at Publisher · View at Google Scholar
  • Pengfei Liu, Liang Xiao, Songze Tang, and Le Sun, “Fractional order variational pan-sharpening,” International Geoscience and Remote Sensing Symposium (IGARSS), vol. 2016-, pp. 2602–2605, 2016. View at Publisher · View at Google Scholar
  • Pushpendra Kumar, Balasubramanian Raman, and Sanjeev Kumar, “A fractional order variational model for the robust estimation of optical flow from image sequences,” Optik, vol. 127, no. 20, pp. 8710–8727, 2016. View at Publisher · View at Google Scholar
  • Weihong Guo, Guohui Song, and Yue Zhang, “PCM-TV-TFV: A Novel Two-Stage Framework for Image Reconstruction from Fourier Data,” SIAM Journal on Imaging Sciences, vol. 10, no. 4, pp. 2250–2274, 2017. View at Publisher · View at Google Scholar
  • Pengfei Liu, Liang Xiao, and Tao Li, “Normal curvature-induced variational model for image restoration,” IET Image Processing, vol. 12, no. 5, pp. 679–689, 2018. View at Publisher · View at Google Scholar
  • Pengfei Liu, Liang Xiao, and Tao Li, “A Variational Pan-Sharpening Method Based on Spatial Fractional-Order Geometry and Spectral–Spatial Low-Rank Priors,” IEEE Transactions on Geoscience and Remote Sensing, vol. 56, no. 3, pp. 1788–1802, 2018. View at Publisher · View at Google Scholar
  • Xiaomei Yang, Yuqing Xiang, Xiujuan Zheng, and Yanan Liu, “Image Deblurring Method with Fractional-order Total Variation and Adaptive Regularization Parameters,” Gongcheng Kexue Yu Jishu/Advanced Engineering Science, vol. 50, no. 6, pp. 205–211, 2018. View at Publisher · View at Google Scholar
  • Dazi Li, Xiangyi Tian, Qibing Jin, and Kotaro Hirasawa, “Adaptive fractional-order total variation image restoration with split Bregman iteration,” ISA Transactions, vol. 82, pp. 210–222, 2018. View at Publisher · View at Google Scholar
  • Wei Wang, Xiang-Gen Xia, Shengli Zhang, Chuanjiang He, and Ling Chen, “Vector Total Fractional-Order Variation and its Applications for Color Image Denoising and Decomposition,” Applied Mathematical Modelling, 2019. View at Publisher · View at Google Scholar
  • Ahlad Kumar, M. Omair Ahmad, and M.N.S Swamy, “A Framework for Image Denoising using First and Second order Fractional Overlapping Group Sparsity (HF-OLGS) Regularizer,” IEEE Access, pp. 1–1, 2019. View at Publisher · View at Google Scholar