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Green Image
Issue No. 06 - June (2010 vol. 32)
ISSN: 0162-8828
pp: 1012-1028
Yu-Wing Tai , Korea Advanced Institute of Science and Technology (KAIST), Korea
Michael S. Brown , National University of Singapore, Singapore
Hao Du , University of Washington, Seattle
Stephen Lin , Microsoft Research Asia, Beijing
We describe a novel approach to reduce spatially varying motion blur in video and images using a hybrid camera system. A hybrid camera is a standard video camera that is coupled with an auxiliary low-resolution camera sharing the same optical path but capturing at a significantly higher frame rate. The auxiliary video is temporally sharper but at a lower resolution, while the lower frame-rate video has higher spatial resolution but is susceptible to motion blur. Our deblurring approach uses the data from these two video streams to reduce spatially varying motion blur in the high-resolution camera with a technique that combines both deconvolution and super-resolution. Our algorithm also incorporates a refinement of the spatially varying blur kernels to further improve results. Our approach can reduce motion blur from the high-resolution video as well as estimate new high-resolution frames at a higher frame rate. Experimental results on a variety of inputs demonstrate notable improvement over current state-of-the-art methods in image/video deblurring.
Motion deblurring, spatially varying motion blur, hybrid camera.
Yu-Wing Tai, Michael S. Brown, Hao Du, Stephen Lin, "Correction of Spatially Varying Image and Video Motion Blur Using a Hybrid Camera", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 32, no. , pp. 1012-1028, June 2010, doi:10.1109/TPAMI.2009.97
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