Non-uniform deblurring for shaken images

Journal article

Photographs taken in low-light conditions are often blurry as a result of camera shake, i.e. a motion of the camera while its shutter is open. Most existing deblurring methods model the observed blurry image as the convolution of a sharp image with a uniform blur kernel. However, we show that blur from camera shake is in general mostly due to the 3D rotation of the camera, resulting in a blur that can be significantly non-uniform across the image. We propose a new parametrized geometric model of the blurring process in terms of the rotational motion of the camera during exposure. This model is able to capture non-uniform blur in an image due to camera shake using a single global descriptor, and can be substituted into existing deblurring algorithms with only small modifications. To demonstrate its effectiveness, we apply this model to two deblurring problems; first, the case where a single blurry image is available, for which we examine both an approximate marginalization approach and a maximum a posteriori approach, and second, the case where a sharp but noisy image of the scene is available in addition to the blurry image. We show that our approach makes it possible to model and remove a wider class of blurs than previous approaches, including uniform blur as a special case, and demonstrate its effectiveness with experiments on synthetic and real images.

Authors: Whyte, O; Sivic, J; Zisserman, A; Ponce, J

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Springer
• Journal: International Journal of Computer Vision
• Volume: 98
• Issue: 2
• Pages: 168-186
• Publication date: 2011-10-27
• Acceptance date: 2011-10-06
• DOI: 10.1007/s11263-011-0502-7
• EISSN: 1573-1405
• ISSN: 0920-5691
• Language: English
• Keywords: SBTMR; camera shake; motion blur; non-uniform/spatially-varying blur; blind deconvolution