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CFA-based Motion Blur Removal
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Pongsak Lasang, Chinphek Ong, and Shengmei Shen
Proc. IEEE International Conference on Consumer Electronics (ICCE’10), January 2010, pp.37-38.
In this paper, a simple and effective motion blur removal method based on long and short exposure images is presented. The long and short exposure images are captured sequentially. Motion pixels between the images are robustly detected, with suppressing noise and preventing artifacts around object boundary. The object motion blur is removed and high quality image is obtained by merging the two images with takes into account the detected motion pixels. The proposed method is directly performed on the CFA (Color Filter Array) image which is only one color component per pixel. It has low computational complexity and memory requirements. The proposed method can achieve HDR (High Dynamic Range) image at the same time.
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