运动模糊图像的运动模糊方向鉴别

曝光瞬间造成图像模糊的运动通常作为直线运动近似处理,若能找出模糊图像的运动模糊方向,并将之旋转到水平轴,则二维问题可简化为一维来处理,大大简化由模糊图像估计出运动模糊点扩散函数以及图像恢复的过程,并为图像恢复的并行计算创造有利条件。由于运动模糊降低了运动方向上图像的高频成分,沿着运动方向实施高通滤波(方向微分),可保证微分图像灰度值(绝对值)之和最小。基于此,本文利用双线性插值的方法,固定并适当选取方向微分的微元大小,构造出3×3方向微分乘子,得到了高效高精度的自动鉴别运动模糊方向的新方法,并通过数值实验进行了验证。

Identification of the Motion Blurred Direction of Motion Blurred Images

The direction of the motion which blurs the image can be dealt with as unchanging during the short exposing time. If it is identified, the blurred direction can be rotated to the horizontal axis, and the image restoration can be worked out easily in one dimension. An excellent simple model for imagery statistics is that of a spatially isotropic first-order Markov process. The autocorrelation of the original image and its power spectrum are assumed to be approximately isotropic. The motion blurring decreases the original image's high frequency contents in the motion direction. Thus, a derivative of the image in the motion direction would suppress more image intensity than a derivation in other direction. Then the motion direction is identified from the blurred image. The derivation matrix is the key for the identification. We select a propriety unchanging step for the direction derivation, a 3×3 direction derivation matrix is then constructed by using the double line interposition. This 3×3 direction derivation matrix can help to identify any motion directions of the most motion blurred images with high precision. It is steady-going.