Image Representation

  • René Vidal
  • Yi Ma
  • S. Shankar Sastry
Part of the Interdisciplinary Applied Mathematics book series (IAM, volume 40)


In this and the following chapters, we demonstrate why multiple subspaces can be a very useful class of models for image processing and how the subspace clustering techniques may facilitate many important image processing tasks, such as image representation, compression, image segmentation, and video segmentation.


Mean Square Error Discrete Cosine Transform Sparse Representation Image Representation Image Patch 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag New York 2016

Authors and Affiliations

  • René Vidal
    • 1
  • Yi Ma
    • 2
  • S. Shankar Sastry
    • 3
  1. 1.Center for Imaging Science Department of Biomedical EngineeringJohns Hopkins UniversityBaltimoreUSA
  2. 2.School of Information Science and Technology ShanghaiTech UniversityShanghaiChina
  3. 3.Department of Electrical Engineering and Computer ScienceUniversity of California BerkeleyBerkeleyUSA

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