确定研究方向后一直在狂补理论，最近看了一些文章，有了些想法，顺便也总结了representation系列的文章，由于我刚接触，可能会有些不足，愿大家共同指正。
从稀疏表示到低秩表示系列文章包括如下内容：
二、NCSR（NonlocallyCentralized Sparse Representation）
三、GHP（GradientHistogram Preservation）
二、 NonlocallyCentralized Sparse Representation
此部分是上篇的续篇，介绍sparse representation 的改进
Related method be supposed: NCSR (ICCV’11, TIP’13)
• A simple but very effective sparserepresentation model was proposed. It outperforms many state-of-the-arts inimage denoising, deblurring and super-resolution.
Related paper:
[1]W. Dong, L. Zhang and G. Shi, “Centralized Sparse Representation for ImageRestoration”, in ICCV 2011.
[2]W. Dong, L. Zhang, G. Shi and X.Li, “NonlocallyCentralized Sparse Representation for Image Restoration”,IEEE Trans. on ImageProcessing,vol. 22, no. 4, pp.1620-1630, April 2013.
NCSR: The idea
NCSR: The objective function
NCSR: The solution
NSCR: The parameters anddictionaries
Denoising results
Deblurring results
未完，待续，更多请关注http://blog.csdn.net/tiandijun，欢迎交流！