The existing super-resolution microscopy technologies based on iterative algorithm to realize super-resolution imaging of fluorescence microscopy and obtain the accurate value of each point center in the fluorescence image by convergence to extreme values are faced with problems such as complex image data fitting process and high computing power requirements. In order to improve the computation speed, a fast point spread function parameter extraction algorithm based on linear regression is proposed, which does not require an iterative process. Experimental results show that the compared with the existing comparison algorithm that can accurately calculate the center position and FWHM (Full Width at Half Maximum) of the image point, although the calculation accuracy is slightly lower, the calculation time of this algorithm is less than 20% of the comparison algorithm. Moreover, the calculation results obtained by this algorithm can be used as the initial parameters of more accurate comparison algorithms, which can reduce the overall calculation time of the comparison algorithm by 30%. This algorithm can also be used as a real-time point spread function FWHM (Full Width at Half Maximum) calculation algorithm, which can be applied to microscope autofocus.