The invention discloses a method for improving video compression coding efficiency based on deep learning. The method comprises the following specific steps of S1, obtaining a peak signal to noise ratio PSNR1 of original video inter-frame prediction composed of basic motion estimation and motion compensation; S2, importing an SRCNN model to train inter-frame pictures, thereby obtaining a weight matrix and a deviation matrix, modifying parameters of the SRCNN model, and adjusting a network to obtain optimal training parameters; S3, testing test pictures through utilization of the trained model,thereby obtaining a result PSNR2 tested by the SRCNN model, and comparing the PSNR1 with the PSNR2, thereby obtaining the feasibility of applying the SRCNN to inter-frame prediction coding; and S4, applying the SRCNN model to official code HM16.0 provided by the newest coding standard HEVC. According to the method, through application of the deep learning to the field of inter-frame coding, the coding efficiency of an inter-frame motion acute block can be improved.