Fast Non-uniform Deblurring using Constrained Camera Pose Subspace

Camera shake during exposure time often results in non-uniform blur across the entire image. Recent algorithms model the non-uniform blurry image as a linear combination of images observed by the camera at discretized poses, and focus on estimating the time fraction positioned at each pose. While these algorithms show promising results, they nevertheless entail heavy computational loads. In this work, we propose a novel single image deblurring algorithm to remove non-uniform blur. We estimate the local blur kernels at different image regions and obtain an initial guess of possible camera poses using backprojection. By restraining the possible camera poses in a low-dimensional subspace, we iteratively estimate the weight for each pose in the camera pose space. Experimental validations with the state-of-the-art methods demonstrate the efficiency and effectiveness of our algorithm for non-uniform deblurring.