Learned Filters

Learned filters

These are examples of 16x16 sparsifying filters, as described in [1]. They were learned on a set of five images and are constrained to form a frame for the space of N by N images. While the filters appear similar to Gabor atoms or the filters learned with a convolutional neural network, they were learned to satisfy a significantly different optimality condition.

  1. L. Pfister and Y. Bresler, “Learning Filter Bank Sparsifying Transforms,” 2018.
    • Abstract
    • arXiv
    • BibTeX