APEX 图像盲复原技术(BIR)往往因算法速度过慢，不稳定或者输入参数过多而难以实时应用。针对这些限制，基于一般BIR 过程中有一个非常重要的属性：降质图像与降质点扩散函数PSF 尺度大小存在强不对称性，提出了多区域参数估计的方法，通过MAP 理论证明了多次参数估计的合理性，并且通过实验说明了多次参数估计方法的可行性。通过多区域参数估计方法，提高了APEX 算法估计参数的精度，进而提高其可用性。通过对仿真图像和实际的图像进行复原处理验证了算法的有效性。该算法速度快、稳定，可用于低噪声高斯类模糊图像实时图像盲复原。

APEX Blind Image Restoration (BIR) is hardly real-time applied in image processing due to its slow speed, instability and the multi-input parameters process. Considering these limitations, according to the very important property in the image restoration process that there is a strong asymmetry between the dimensionality of the image and the Point Spread Function (PSF), the multi-region parameters estimate (MRPE) process is proposed, and the rationality of the MRPE process was proved by the Maximum-a-posteriori (MAP) estimate theory, and the feasibility of the multi-estimate process is illuminated by the experiments. Through the MRPE process method, the precision of the parameter estimation and usability are improved, and validity of the algorithm is validated by the experiments. This method is fast and robust, and can be applied for the low level noisy Gauss class blur image real-time image restoration.