针对部分景观运动模糊的还原算法

Restoration algorithm for partial landscape motion blurred

图像复原是图像处理中的重要分支,对于由于相机曝光时间导致的局部模糊使得照片无法使用的情况,通过对图像质量进行改善而使得图像能够被正常使用。运动模糊图像处理的难题主要体现在多角度的加速度上。针对匀速运动的部分景观运动模糊图像,首先用懒惰抠图技术提取模糊区域,再提出一种方法估算模糊角度和模糊长度并计算相应的点扩散函数,最后通过已知的参数依靠matlab建立合适的维纳滤波模型进行复原仿真。分析恢复图像和原图的质量数据,表明提出的复原模型的恢复效果拥有较好的准确性和实用性。但对于一些复杂噪声,需要优化算法去减小影响。

Image restoration is an important branch in image processing.For local blurring caused by camera exposure time,photos cannot be used.The purpose is to improve image quality without affecting normal use.Motion blurred images often include multi-angle acceleration,which is a problem in image processing.For the partial landscape motion blur image of uniform motion,firstly,the fuzzy region is extracted by the lazy mapping technique.Then a method is proposed to estimate the blur angle and the blur length and calculate the corresponding point spread function.Finally,the known parameters are used to establish a suitable The Wiener filtering model is used for restoration simulation.The quality data of the restored image and the original image are analyzed,which indicates that the restoration effect of the proposed restoration model has better accuracy and practicability.But for some complex noise,you need to optimize the algorithm to reduce the impact.