compressive sensing

呃，我很无奈的表示，我必须要学习这个理论了。Candès和陶哲轩大牛开创的这个领域，还是很新颖，很前沿的。 Yi Ma大牛在这方面也有突出贡献啊。 唉，一点点儿开始看吧。我作为一个数学傻人，先搞明白L1 Minimization 再说吧。 bless

 

入门级读物：

Fill in the Blanks: Using Math to Turn Lo-Res Datasets Into Hi-Res Samples [ http://songshuhui.net/archives/35169]

[小红猪]压缩感知与单像素照相机 [http://songshuhui.net/archives/11006]

 

注释：

the theory of compressed sensing implies that the precise choice of feature space is no longer critical: even random features contain enough information to recover the sparse representation and hence correctly classify any test image. What is critical is that the dimension of the feature space is sufficiently large, and that the sparse representation is correctly computed.  -------from PAMI08 "Robust Face Recognition via Sparse Representation" J. Wright et al.

 

按照这个说法，选神马feature不重要，只要维度够高。