Figure 3. Samples from model trained on natural images.

(A) To visualize the contribution of the different MCGSMs at the different scales, the first column shows samples from the MCGSM at the largest scale (low resolution). This sample was obtained using the top layer single-scale MCGSM. The second column shows samples from the full model, conditionally sampled with respect to the sample on the left. These samples therefore also contain the high-resolution information. The image on the left can be recovered from the image on the right through block-averaging. (B) The third column shows the same samples with all higher-order correlations destroyed but the autorocorrelation function left intact. This shows that the characteristic features of our samples are due to learned higher-order correlations and that the second-order correlations of natural images are faithfully reproduced as well. (C) For comparison, the right most column shows examples of images from the training set [14].