Zhaowen Wang, Jianchao Yang, Haichao Zhang, Zhangyang Wang *, Yingzhen Yang, Ding Liu and Thomas. S. Huang,

"Sparse Coding and Its Applications in Computer Vision"

World Scientific Books, 2015. ISBN: 978-981-4725-04-0.  [Amazon Link]

* Zhangyang Wang is the sole author of:

   - Chapter 8. "Hyper-Spectral Image Modeling"

   as well as a major co-author of:

   - Chapter 3. "Image Super Resolution"

  -  Chapter 6. "Clustering"



Sparse coding is an important model to represent visual information. By exploiting the latent structure of natural images in low dimensional subspaces, sparse coding has achieved great success in many image processing and understanding tasks. In this monograph, we have an in-depth analysis of the working mechanism of sparse coding based on the prior theoretical and empirical studies. We also review various applications of sparse coding including object recognition, sensor fusion, super-resolution, de-blurring and hyper-spectral signal processing, with special emphasis on learning the sparse representation in specific task domain. Also discussed is the connection between sparse coding and deep networks, which are currently the best performers in computer vision. Such connection sheds some light on the future direction of  using sparse coding in problems with larger scale and higher complexity.

Zhangyang (Atlas) Wang​