Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2013, Article ID 751716, 11 pages
http://dx.doi.org/10.1155/2013/751716
Research Article

Analysis and Denoising of Hyperspectral Remote Sensing Image in the Curvelet Domain

1College of Science, National University of Defense Technology, Changsha, Hunan 410073, China
2Department of Radiation Oncology, The 89th Hospital of PLA, Weifang, Shandong 261045, China

Received 7 May 2013; Accepted 1 July 2013

Academic Editor: Yue Wu

Copyright © 2013 Dong Xu 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 [8 citations]

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

  • Sergey K. Abramov, Mykhail L. Uss, Victoriya V. Abramova, Vladimir V. Lukin, Benoit Vozel, and Kacem Chehdi, “On noise properties in hyperspectral images,” 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), pp. 3501–3504, . View at Publisher · View at Google Scholar
  • Xiujie Qu, Fu Zhang, and Huan Jia, “An Efficient Adaptive Denoising Algorithm for Remote Sensing Images,” Mathematical Problems in Engineering, vol. 2013, pp. 1–5, 2013. View at Publisher · View at Google Scholar
  • Minchao Ye, Yuntao Qian, and Jun Zhou, “Multitask Sparse Nonnegative Matrix Factorization for Joint Spectral-Spatial Hyperspectral Imagery Denoising,” Ieee Transactions On Geoscience And Remote Sensing, vol. 53, no. 5, pp. 2621–2639, 2015. View at Publisher · View at Google Scholar
  • Deeksha Bhardwaj, and Nilima A. Bandane, “Improved Hyperspectral Image Denoising Employing Sparse Representation,” Proceedings - 2015 International Conference on Computational Intelligence and Communication Networks, CICN 2015, pp. 475–480, 2016. View at Publisher · View at Google Scholar
  • Guangchun Luo, Guangyi Chen, Shen-En Qian, Ling Tian, and Ke Qin, “Minimum Noise Fraction versus Principal Component Analysis as a Preprocessing Step for Hyperspectral Imagery Denoising,” Canadian Journal of Remote Sensing, vol. 42, no. 2, pp. 106–116, 2016. View at Publisher · View at Google Scholar
  • Lei Sun, and Dong Xu, “Hyperspectral image denoising using multiple linear regression and bivariate shrinkage with 2-D dual-tree complex wavelet in the spectral derivative domain,” Boletim de Ciencias Geodesicas, vol. 22, no. 4, pp. 822–834, 2016. View at Publisher · View at Google Scholar
  • Tong Qiao, Jinchang Ren, Zheng Wang, Jaime Zabalza, Meijun Sun, Huimin Zhao, Shutao Li, Jon Atli Benediktsson, Qingyun Dai, and Stephen Marshall, “Effective Denoising and Classification of Hyperspectral Images Using Curvelet Transform and Singular Spectrum Analysis,” IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 1, pp. 119–133, 2017. View at Publisher · View at Google Scholar
  • Jayaprakash Chippy, Naveen Varghese Jacob, R.K. Renu, V Sowmya, and K.P. Soman, “Least Square Denoising in Spectral Domain for Hyperspectral Images,” Procedia Computer Science, vol. 115, pp. 399–406, 2017. View at Publisher · View at Google Scholar