Right after the announcement of the latest version of Accelerate I like to announce an application build using that framework: "patch-image" assembles a big image from several overlapping parts. http://hackage.haskell.org/package/patch-image Now, let me extract the beginning of the docs: Compose a collage from overlapping image parts. In contrast to Hugin, this is not intended for creating panoramas from multiple photographies, but instead is specialised to creating highly accurate reconstructions of flat but big image sources, like record covers, posters or newspapers. It solves the problem that your scanner may be too small to capture a certain image as a whole. . This is the workflow: Scan parts of an image that considerably overlap. They must all be approximately oriented correctly. The program uses the overlapping areas for reconstruction of the layout of the parts. If all parts are in the directory @part@ then in the best case you can simply run: .

patch-image --output=collage.jpeg part/*.jpeg . If you get blurred areas, you might enable an additional rotation correction: . patch-image --finetune-rotate --output=collage.jpeg part/*.jpeg

Currently it depends on CUDA although this is not strictly necessary.