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Computational Photography

New cameras don't just capture photons; they compute pictures

Brian Hayes

Beyond Photorealism

Computational photography is currently a hot topic in computer graphics. (Computer devoted a special issue to the subject in 2006.) There's more going on than I have room to report, but I want to mention two more particularly adventurous ideas.

Diagrammatic renderingClick to Enlarge ImageOne of these projects comes from Raskar and several colleagues (Kar-Han Tan of Mitsubishi, Rogerio Feris and Matthew Turk of the University of California, Santa Barbara, and Jingyi Yu of MIT). They are experimenting with "non-photorealistic photography"—pictures that come out of the camera looking like drawings, diagrams or paintings.

For some purposes a hand-rendered illustration can be clearer and more informative than a photograph, but creating such artwork requires much labor, not to mention talent. Raskar's camera attempts to automate the process by detecting and emphasizing the features that give a scene its basic three-dimensional structure, most notably the edges of objects. Detecting edges is not always easy. Changes in color or texture can be mistaken for physical boundaries; to the computer, a wallpaper pattern can look like a hole in the wall. To resolve this visual ambiguity Raskar et al. exploit the fact that only physical edges cast shadows. They have equipped a camera with four flash units surrounding the lens. The flash units are fired sequentially, producing four images in which shadows delineate changes in contour. Software then accentuates these features, while other areas of the image are flattened and smoothed to suppress distracting detail. The result is reminiscent of a watercolor painting or a drawing with ink and wash.

Another wild idea, called dual photography, comes from Hendrik P. A. Lensch, now of the Max-Planck-Institut für Informatik in Saarbrucken, working with Stephen R. Marschner of Cornell University and Pradeep Sen, Billy Chen, Gaurav Garg, Mark Horowitz and Marc Levoy of Stanford. Here's the setup: A camera is focused on a scene, which is illuminated from another angle by a single light source. Obviously, a photograph made in this configuration shows the scene from the camera's point of view. Remarkably, though, a little computation can also produce an image of the scene as it would appear if the camera and the light source swapped places. In other words, the camera creates a photograph that seems to be taken from a place where there is no camera.

This sounds like magic, or like seeing around corners, but the underlying principle is simple: Reflection is symmetrical. If the light rays proceeding from the source to the scene to the camera were reversed, they would follow exactly the same paths in the opposite direction and return to their point of origin. Thus if a camera can figure out where a ray came from, it can also calculate where the reversed ray would wind up.

Sadly, this research is not likely to produce a camera you can take outdoors to photograph a landscape as seen from the sun. For the trick to work, the light source has to be rather special, with individually addressable pixels. Lensch et al. have adapted a digital projector of the kind used for PowerPoint presentations. In the simplest algorithm, the projector's pixels are turned on one at a time, in order to measure the brightness of that pixel in "reversed light." Thus we return to the thought experiment  where each of a million pixels in a display shines on each of a million photosites in a sensor. But now the experiment is done with hardware and software rather than thoughtware.

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