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.