非零边界旋转运动模糊图像的恢复算法

具有非零灰度边界的旋转运动模糊图像的恢复是图像处理的一个热点研究问题。为了在离散情况下能够沿模糊路径上快速提取像素的灰度信息，将Bresenham算法思想引入到旋转运动模糊图像的恢复工作中，并在此基础上，提出了一种基于模糊路径频域滤波去卷积的恢复算法，同时，为了有效地恢复非零边界区的图像信息，又提出了一种基于邻域知识引导的最小代价恢复算法。这样就可将非零边界旋转运动模糊图像的恢复过程分为两个阶段，即先后用该两个恢复算法分别进行处理，由于使整个恢复过程避开了迭代计算和一些复杂的费时运算，从而加快了恢复速度。为验证该算法的效果，在微机上，对该恢复算法与现有的算法进行了对比实验和一系列的验证实验，实验结果表明，该算法十分有效，且具有一定的抗噪能力。

Restoration Algorithm for Rotational Motion Blurred Images with Non-zero Boundary

The restoration of rotational motion blurred images with the boundaries of non zero gray values is a study hotshot in the field of image processing. In order to quickly fetch the gray values of pixels along the blurring paths in the case of discreteness, the idea of Bresenham algorithm is incorporated into the process of restoration of rotational motion blurred image. The restoration algorithm based on deconvolution along the blurring path by mean of filtering in frequency domain is proposed. Meanwhile, in order to effectively restore the information of pixels in the boundary area, the less cost restoration algorithm based on knowledge guide is also proposed?Thus, the restoration of the blurred image with non zero boundary consists of two stages, in which the two proposed restoration algorithms are employed. On the other hand, the iterative calculation and complicated time consuming operations are avoided to speed up the image restoration. The effect of the proposed algorithms is validated by comparison experiments and a lot of test experiments in the microcomputer, and experimental results illustrate that the proposed algorithms are efficient and capable of resisting noise.