Aim at the shortcomings that the mathematical model for the measurement of far-field focal spot with high dynamic range does not consider the influence of noise on the measurement results， this paper optimizes the measurement method of far-field focal spot based on schlieren from three aspects. Firstly， the mathematical model for the measurement of far-field focal spot based on schlieren is improved， and the noise is added to the mathematical model， which makes the mathematical model match with the real experimental environment， and improves the practicability and theoretical support of the mathematical model； Secondly， the denoising algorithm based on Convolution Neural Network （DnCNN） is used in the de-noise processing of the main lobe and side lobe CCD image， and the original denoising algorithm is improved effectively in this paper， which can remove the noise of different levels （0~75 dB） of the mainlobe and sidelobe 12-bit images； Finally， the whole experimental process of far-field focal spot measurement is simulated， including light splitting， attenuation， adding noise， schlieren sphere occlusion， denoising， attenuation magnification， focal spot reconstruction， etc.， and the effective experimental results of reconstructed focal spot is obtained， which the correlation coefficient between the reconstructed and theoretical focal spot images is 0.998 9， and the error of dynamic range between the reconstructed and theoretical focal spot is 3.22%. The simulation results show that through the improvement of the mathematical model and the DnCNN denoising algorithm， the necessity of the improved mathematical model and the superior performance of the DnCNN denoising algorithm in improving the accuracy of the two-dimensional distribution and dynamic range of reconstructed focal spot are verified. The reliability of the measurement of far-field focal spot with high dynamic range based on schlieren is improved， and the accuracy and efficiency of the measurement of far-field focal spot in high dynamic range is met in the end.