Trainlets: Dictionary Learning in High Dimensions

The work reported in this paper describes a novel Dictionary Learning (DL) algorithm that is capable of handling very large image patches. Whereas classical DL algorithms, such as K-SVD, can handle small image patches (e.g., 8-by-8 pixels), this new Online Sparse Dictionary Learning (OSDL) can operates on small images of size 64-by-64 while still being very effective and relatively quick. This is achieved by harnessing three key ingredients: (i) The learned dictionary is structured, formed as a multiplication of a fixed dictionary by a sparse matrix; (ii) The chosen fixed dictionary is a cropped wavelet that exhibit no boundary problems; and (iii) In order to learn rather quickly, an online scheme for this DL is proposed. The following freely available package contains our Matlab code to apply this algorithm and reproduce the results in the above-mentioned paper.