Removing Non-Uniform Motion Blur from Images Export

@proceedings{citeulike:3181293, abstract = {We propose a method for removing non-uniform motion blur from multiple blurry images. Traditional methods focus on estimating a single motion blur kernel for the entire image. In contrast, we aim to restore images blurred by unknown, spatially varying motion blur kernels caused by different relative motions between the camera and the scene. Our algorithm simultaneously estimates multiple motions, motion blur kernels, and the associated image segments. We formulate the problem as a regularized energy function and solve it using an alternating optimization technique. Real- world experiments demonstrate the effectiveness of the proposed method.}, author = {Cho, Sunghyun and Matsushita, Y. and Lee, Seungyong}, booktitle = {Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on}, citeulike-article-id = {3181293}, citeulike-linkout-0 = {http://dx.doi.org/10.1109/ICCV.2007.4408904}, citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4408904}, doi = {10.1109/ICCV.2007.4408904}, journal = {Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on}, keywords = {partial}, pages = {1--8}, posted-at = {2008-09-02 11:09:11}, priority = {2}, title = {Removing Non-Uniform Motion Blur from Images}, url = {http://dx.doi.org/10.1109/ICCV.2007.4408904}, year = {2007} }

TY - CONF ID - citeulike:3181293 L3 - citeulike-article-id:3181293 N2 - We propose a method for removing non-uniform motion blur from multiple blurry images. Traditional methods focus on estimating a single motion blur kernel for the entire image. In contrast, we aim to restore images blurred by unknown, spatially varying motion blur kernels caused by different relative motions between the camera and the scene. Our algorithm simultaneously estimates multiple motions, motion blur kernels, and the associated image segments. We formulate the problem as a regularized energy function and solve it using an alternating optimization technique. Real- world experiments demonstrate the effectiveness of the proposed method. JF - Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on EP - 8 TI - Removing Non-Uniform Motion Blur from Images T2 - Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on SP - 1 KW - partial AU - Cho, Sunghyun AU - Matsushita, Y AU - Lee, Seungyong PY - 2007/// UR - http://dx.doi.org/10.1109/ICCV.2007.4408904 ER -