经典的图像恢复算法设点扩展函数（PSF)是已知的,然而在许多情况下PSF难以确定,不得不在只知道成像系统部分信息甚至没有任何信息的情况下估计真实图像和PSF,这一过程称为图像盲复原。对于高斯模糊图像,它的PSF是很难被检测出来的,因此高斯模糊图像的盲复原一直是个棘手的问题。利用高斯点扩展函数的特性,初始估计PSF并对加噪后的模糊图像进行维纳滤波,后经过中值滤波获得恢复图像。恢复的图像主观视觉效果较好,具有良好的抗噪性,复原效果明显。该方法对于提高图像质量有一定的参考价值。

Classical image restoration algorithm is based on point spread function (PSF) is known. However, it is difficult to determine PSF in many cases, we have to estimate the true image and PSF in the case of only knowing some of the information or no information of imaging systems, this process is called blind image restoration. For the Gaussian blurred image, it is very difficult to detect PSF, so blind restoration of the Gaussian blurred image has been a troublesome issue. In this paper, we suppose the initial PSF using the characteristics of Gaussian PSF, and do Wiener filtering based on Gaussian blurred image with noise, then gain the restoration image through the median filtering. Experiment shows that, restored image is better in subjective visual effect, and remarkable in recovery effect with good noise immunity. This method has some reference value to improve the image quality.