Analyzing Spatially-varying Blur

Blur is caused by a pixel receiving light from multiple scene points, and in many cases, such as object motion, the induced blur varies spatially across the image plane. However, the seemingly straight-forward task of estimating spatially-varying blur from a single image has proved hard to accomplish reliably. This work considers such blur and makes two contributions: a local blur cue that measures the likelihood of a small neighborhood being blurred by a candidate blur kernel; and an algorithm that, given an image, simultaneously selects a motion blur kernel and segments the region that it affects. The methods are shown to perform well on a diversity of images.

• Type: Conference
• Year: 2010
• Where: CVPR
• Authors: Ayan Chakrabarti, Todd Zickler, William Freeman
• Keywords: Blur Kernel, Blur Varies, Computer Vision, CVPR 2010, Local Blur Cue