从稀疏表示到低秩表示(三)
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)
三、GHP(GradientHistogram Preservation)
此部分是上篇的续篇,介绍sparse representation 的改进
GHP(CVPR’13, TIP’14)
• Like noise, textures are fine scale structures in images,and most of the denoising algorithms will remove the textures while removingnoise.
• Is it possibleto preserve the texture structures, to some extent, in denoising?
• We made a goodattempt in:
[1] W. Zuo, L. Zhang, C. Song, and D. Zhang, “Texture Enhanced Image Denoisingvia
Gradient Histogram Preservation,” in CVPR 2013.
[2] W. Zuo, L. Zhang, C. Song, D. Zhang, and H.Gao, “GradientHistogram Estimation
and Preservation for Texture Enhanced Image Denoising,” in TIP 2014.
GHP
GHP results: CVPR’13 logo
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