图像复原技术在航空拍摄和机器视觉中是提高图像质量的重要手段.针对有相对运动情况的图像存在的降质模糊,分析了运动模糊的数学原理,针对不同运动模糊采取了不同去模糊方式.即先判断图像存在的运动模糊方式,针对直线运动通过Hough变换法和误差参数法相结合的方法估计降质参数,而对于旋转运动则采用曲线拟合和极坐标转换相结合的方法来估计降质参数.通过维纳滤波方法复原图像,提高图像质量.利用提出的自适应方法对直线运动模糊(参数为(30,70°))和旋转运动模糊(参数为(128,128),20°)分别作了实验计算.对比实验表明,这种由粗及精的方法能准确估计模糊参数,与传统处理方法相比,更加便捷有效.%The image restoration technique is an important way to improve the quality of images, especially in flight photography and machine vision. In this paper, the mathematic principle was analyzed first, and then different de-blurring methods were employed correspondingly for each motion condition; specifically, the type of motion blur was judged. For linear motion blur, both the Hough transform and error-parameter were taken to estimate parame-ters. Furthermore, for rotational motion blur, the curve-fitting and polar transform were combined to estimate de-graded parameters. Both were followed by Wiener filtering to recover images and improve image vision quality. The proposed adaptive algorithm was used to calculate the linear motion blur parameter (30,70°) and rotational motion blur parameter ((128,128) , 20°). The results show that the algorithm can estimate blur parameters accurately. Compared with traditional handling, this proposed method has the advantages of high precision, robustness, and speed.
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