Robust destriping of MODIS and hyperspectral data using a hybrid unidirectional total variation model
作者: Gang ZhouHouzhang FangCen LuSiyue WangZhiyong ZuoJing Hu
作者单位: 1Science and Technology on Multi-spectral Information Processing Laboratory, School of Automation, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
2National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China
刊名: Optik - International Journal for Light and Electron Optics, 2015, Vol.126 (7-8), pp.838-845
来源数据库: Elsevier Journal
DOI: 10.1016/j.ijleo.2015.02.045
关键词: Stripe noiseDestripingHybrid unidirectional total variation modelSplit Bregman iteration
原始语种摘要: Abstract(#br)Imaging from a degenerated push broom scanner usually leads to an undesired stripe noise which seriously affected the image quality. To eliminate this kind of artifact, a robust hybrid unidirectional total variation model is presented. The traditional unidirectional total variation model produces an excellent performance only on weak and moderate-amplitude stripe images while does a poor job on heavy ones. By introducing a simple weighted matrix, a hybrid unidirectional total variation model with two combined ℓ 1 data-fidelity terms is launched to handle various stripe noises with different intensity. An efficient numerical algorithm based on the split Bregman iteration is developed to solve the hybrid ℓ 1 -regularized optimization problem. Comparative results on simulated...
全文获取路径: Elsevier  (合作)

  • variation 变异
  • unidirectional 单向的
  • model 模型
  • total 总和
  • artifact 人工产物
  • scanner 扫描设备
  • preserve 保存
  • efficient 有用的
  • detail 详情
  • iteration 迭代