计算机科学 ›› 2024, Vol. 51 ›› Issue (11A): 231200046-9.doi: 10.11896/jsjkx.231200046
朱沛伍, 高树辉, 谢昭宇, 傅裕
ZHU Peiwu, GAO Shuhui, XIE Zhaoyu, FU Yu
摘要: 车辆是刑事案件中常使用的工具,车牌识别是涉案车辆认定的重要依据之一,因此对运动模糊造成的车牌图像退化的复原是刑事技术工作的重要研究方向。文中提出一种基于频率域点扩散函数参数估计的车牌图像复原算法,运用二维离散傅里叶变换、Radon变换以及Wiener滤波算法解决监控视频视角下运动模糊车牌的复原问题。通过预处理对运动模糊图像进行灰度化和降噪,并对图像添加Hanning窗,进行二维离散傅里叶变换和对数运算,计算图像的功率频谱图,运用Radon变换对频谱图进行检测,估算模糊方向;对频谱图进行最小值计算,求模糊长度,完成对点扩散函数两个参数的估算。通过Wiener滤波算法进行图像反卷积,实现图像复原。针对传统频谱图估算模糊参数易受中央亮线干扰的问题,在离散傅里叶变换之前添加窗函数进行优化。使用道路监控拍摄的模糊图像,进行点扩散函数参数估计实验,同时与目前未加窗的方法进行对比,验证所提算法的复原效果。实验结果证明,所提算法在复原车牌图像语义信息方面具有优势,能为刑事图像技术领域模糊车牌复原提供方法补充。
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