Abstract

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.

Downloads

	PDF version of our SIGGRAPH paper (10MB) Download Adobe Acrobat Reader 7
	New: PDF of slides for 1 hour presentation (28MB) Shorted Powerpoint slides from SIGGRAPH presentation (59MB) Videos from the presentation: Slow motion, pt.1 (wmv, 4.3MB), Slow motion, pt.2 (wmv, 10.5MB) Camera Trajectory (avi, 4.9MB), Normal speed (wmv, 4.6MB) ** A zip file including ppt and all the videos (78MB)
	Some pictures from the paper (11.8MB) Includes inferred blur kernels. N.B. Please take care not to compress the images - compression artifacts look very much like blur. I will add more images to the ZIP file as I get permission from their owners. If you are from the media, please email me before using them.
	Download Matlab source code: zip Here is the accompanying README file.

Acknowledgements

Last update: Aug 3, 2006. Thanks for Ce Liu for the page format.