Sorel Michal, Flusser Jan
Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic, Prague 8, Czech Republic.
IEEE Trans Image Process. 2008 Feb;17(2):105-16. doi: 10.1109/TIP.2007.912928.
We examine the problem of restoration from multiple images degraded by camera motion blur. We consider scenes with significant depth variations resulting in space-variant blur. The proposed algorithm can be applied if the camera moves along an arbitrary curve parallel to the image plane, without any rotations. The knowledge of camera trajectory and camera parameters is not necessary. At the input, the user selects a region where depth variations are negligible. The algorithm belongs to the group of variational methods that estimate simultaneously a sharp image and a depth map, based on the minimization of a cost functional. To initialize the minimization, it uses an auxiliary window-based depth estimation algorithm. Feasibility of the algorithm is demonstrated by three experiments with real images.
我们研究了从因相机运动模糊而退化的多幅图像进行恢复的问题。我们考虑具有显著深度变化从而导致空间可变模糊的场景。如果相机沿着与图像平面平行的任意曲线移动且无任何旋转，所提出的算法均可应用。无需相机轨迹和相机参数的知识。在输入时，用户选择一个深度变化可忽略不计的区域。该算法属于变分方法组，基于代价泛函的最小化同时估计清晰图像和深度图。为初始化最小化，它使用一种基于辅助窗口的深度估计算法。通过对真实图像的三个实验证明了该算法的可行性。
