The invention relates to a finite angle projection reconstruction method based on double regular item optimization of L0 norm and singular value threshold decomposition, and belongs to the field of image processing. The method specifically comprises the following steps: S1, establishing an optimization problem target equation according to a CT imaging principle, a regularization framework and a projection data set P; S2, initializing parameters; S3, performing iteration by adopting a SART algorithm to obtain an image X, and correcting the X through error feedback; S4, performing gradient L0 norm optimization on the corrected image X to obtain an image XL0, and updating an error d1; S5, performing singular value decomposition on the image optimized in the step S4, adding a soft threshold constraint to optimize the image to obtain an XSVT, and updating an error d2; and S6, carrying out next round of iteration on the image obtained in the step S5 according to the step S3 until an iteration termination condition is met. According to the method, the CT image contour can be effectively recovered, finite angle artifacts are reduced, and therefore the finite angle CT imaging quality and applicability are improved.