In order to reduce the noise of coronary angiography image sequence, enhance the diagnostic accuracy for coronary heart disease, and eventually acquire superior image quality under low X-ray dose, a method of spatial-temporal filtering for coronary angiography images was proposed. By introducing the idea of threshold noising in wavelet denoising into the Fast Discrete Orthonormal Stockwell Transform (FDOST), a soft-threshold denoising algorithm based on FDOST was proposed for the spatial denoising of coronary angiography images. The conventional wavelet denoising was used for temporal denoising of coronary angiography images, taking advantage of its time smoothing feature. Hessian matrix was used in pre-processing to track the line-like structure of coronary angiography images. The simulation and experimental results show that the signal-to-noise ratio and contrast-to-noise ratio of the denoised images are improved significantly compared with the original image, and the proposed method is suitable for the denoising of low-dose coronary angiography image sequence.