Paper Title: Super-Resolution via Recapture and Bayesian Effect Modeling
Authors: Neil Toronto, Bryan S. Morse, Kevin Seppi, Dan Ventura
Paper ID 1062

This supplementary material contains:
 - The 7 original test set images and the double decimations of them used in Ouwerkerk's 2006 survey.
 - 4x super-resolution results using Bayesian edge inference (BEI - ours), local correlation (LCSR) and resolution synthesis (RS).
 - Additional examples of CCD demosaicing and inpainting using BEI.

All images are full-resolution and are stored with lossless compression in Portable Network Graphics (PNG) format.

We have at our disposal the complete super-resolution results for every method tested in Ouwerkerk's survey as well as our results for BEI. We have left most out due to space constraints, but we plan to make them available online as a public resource.

Directory "originals" contains the original images "*512.png" and double decimations "*128.png".

Directory "128_4x" contains the results of applying LCSR, RS and BEI (with noisy recapture) to double-decimated test set images, with scaling factor 4x.

Directory "masks" contains "Bayer512.png", a missing data mask that simulates a Bayer filter, which is used for CCD demosaicing, and "Text512.png", the missing data mask used for inpainting.

Directory "ccd" shows BEI's reconstruction after simulating a Bayer filter ("masks/Bayer512.png"). For each image, it contains the available data "*512bayer.png", BEI's reconstruction "*512bei.png", and the result of cubic interpolation "*512cubic.png".

Directory "inpaint" shows BEI's reconstruction after defacement ("masks/Text512.png"). For each image, it contains the available data "*512defaced.png" (missing data is white) and BEI's reconstruction "*512bei.png".
