Without specialized sensor technology or custom, multi-chip cameras, high dynamic range imaging typically involves time-sequential capture of multiple photographs. The obvious downside to this approach is that it cannot easily be applied to images with moving objects, especially if the motions are complex.
In this paper, we take a novel view of HDR capture, which is based on a computational photography approach. We propose to first optically encode both the low dynamic range portion of the scene and highlight information into a low dynamic range image that can be captured with a conventional image sensor. This step is achieved using a cross-screen or "star" filter. Second, we decode, in software, both the low dynamic range image and the highlight information. Lastly, these two portions can be combined to form an image of a higher dynamic range than the regular sensor dynamic range.
This work was supported by Dolby under the Dolby Research Chair in Computer Science at UBC.
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