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Image deblurring to remove blur caused by camera shake has been intensively studied. Nevertheless, most methods are brittle and computationally expensive. In this paper we analyze multi-image approaches, which capture and combine multiple frames in order to make deblurring more robust and tractable. In particular, we compare the performance of two approaches: align-and-average and multi-image deconvolution. Our deconvolution is nonblind, using a blur model obtained from real camera motion asdoi:10.1109/cvpr.2014.430 dblp:conf/cvpr/ParkL14 fatcat:jdlnwnf7mzhmdkk7wodairqnli