Exposure Stacks for Live Scenes with Hand-held Cameras

Many computational photography applications require the user to take multiple pictures of the same scene with different camera settings. While this allows to capture more information about the scene than what is possible with a single image, the approach is limited by the requirement that the images be perfectly registered. In a typical scenario the camera is hand-held and is therefore prone to moving during the capture of an image burst, while the scene is likely to contain moving objects. Combining such images without careful registration introduces annoying artifacts in the final image.

This paper presents a method to register exposure stacks in the presence of both camera motion and scene changes.


Jun Hu (Duke University)
Kari Pulli (NVIDIA)

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