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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!
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原文地址:http://www.cnblogs.com/yymn/p/4589460.html