Abstract

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 as measured by a gyroscope. We show that in most situations such deconvolution outperforms align-and-average. We also show, perhaps surprisingly, that deconvolution does not benefifit from increasing exposure time beyond a certain threshold. To demonstrate the effectiveness and effificiency of our method, we apply it to still-resolution imagery of natural scenes captured using a mobile camera with flflexible camera control and an attached gyroscope