Journal
ACM TRANSACTIONS ON GRAPHICS
Volume 25, Issue 3, Pages 787-794Publisher
ASSOC COMPUTING MACHINERY
DOI: 10.1145/1141911.1141956
Keywords
camera shake; blind image deconvolution; variational learning; natural image statistics
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Camera shake during exposure leads to objectionable image blur and ruins many photographs. Conventional blind deconvolution methods typically assume frequency-domain constraints on images, or overly simplified parametric forms for the motion path during camera shake. Real camera motions can follow convoluted paths, and a spatial domain prior can better maintain visually salient image characteristics. We introduce a method to remove the effects of camera shake from seriously blurred images. The method assumes a uniform camera blur over the image and negligible in-plane camera rotation. In order to estimate the blur from the camera shake, the user must specify an image region without saturation effects. We show results for a variety of digital photographs taken from personal photo collections.
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