Nonlinear spike-and-slab sparse coding for interpretable image encoding. PLOS ONE

From this original noise-free image, we cut a 110 × 110 pixel occlusion-rich section and scaled it up to 256 × 256 pixels to use in our dataset. To compose the dataset, we cut the 256 × 256 image (with pixel values ranging from (0, 255)) into N = 61009 overlapping image patches of D = 9 × 9 pixels, then add independent Gaussian noise with σ = 5.

In the corresponding publication, the data is shown in Figure8A-B. [33] Mairal, J., Bach, F., Ponce, J., Sapiro, G., and Zisserman, A. (2009): Non-local sparse models for image restoration. International Conference on Computer Vision 25.