提出了一种基于模糊成像机理的QR码图像快速盲复原方法。在对模糊成像弥散光斑质心不变性研究的基础上，设计圆形寻像图形，在成像模糊时能通过连通域等方法快速检测到图形质心以及QR码符号位置，再结合阶跃边缘特性、梯度强度特性、边缘检测技术以及光学成像机理快速准确估计出模糊QR码图像离焦半径大小，应用维纳滤波算法快速且有效复原QR码图像。与对比算法相比，本文算法在结构相似性和峰值信噪比上都有提升，特别是在复原速度上有显著提高，其平均复原时间为0.329 2 s。该方法能够以较高的精度估算出离焦半径大小，并能快速实现QR码图像的盲复原，具有快速性及稳健性优势，便于嵌入式硬件实现，能较好适用于条码标识相关的工业物联网应用场景。

A fast blind restoration method of QR code images was proposed based on a blurred imaging mechanism. On the basis of the research on the centroid invariance of the blurred imaging diffuse light spots， the circular finder pattern is designed. When the image is blurred， the centroid of the pattern and the position of the QR code symbol can be quickly detected by methods such as connected components. Moreover， combined with step edge characteristics， gradient and intensity characteristics， edge detection technology， and optical imaging mechanism， the defocus radius of the blurred QR code image can be quickly and accurately estimated. Furthermore， the Wiener filter is applied to restore the QR code image quickly and effectively. Compared with the other algorithms， the proposed method has improved deblurring results in both structural similarity and peak signal-to-noise ratio， especially in the recovery speed. The average recovery time is 0.329 2 s. Experimental results show that this method can estimate the defocus radius with high accuracy and can quickly realize the blind restoration of QR code images. It has the advantages of rapidity and robustness， which are convenient for embedded hardware implementation and suitable for barcode identification-related industrial Internet of Things application scenarios.