Light-field （LF） imaging can capture spatial and angular information of light rays in a scene. Compared to traditional 2D/3D images， LF images provide a more comprehensive description of the scene. To address the problem of low angular resolution in LF images caused by hardware constraints， a LF angular super-resolution reconstruction method based on the fusion of 3D epipolar plane images （EPIs） is proposed. First， to make full use of the parallax information of the input images and improve the accuracy of depth estimation， the input images are arranged in varying parallax directions， and their features are extracted individually. Then， initial synthetic LF images are generated by transforming the input images to match the new viewpoint location using the corresponding depth maps. Finally， to ensure that the reconstructed LF image retains better detail information and geometric consistency， the LF is reconstructed horizontally and vertically via the horizontal and vertical 3D EPI fusion reconstruction branches， respectively. These two reconstruction results are then fused to produce the final high-angular-resolution LF image. Experimental results show that， compared to existing methods， the proposed method achieves an improved reconstruction quality across both synthetic and real-world LF image datasets， and the maximum increase in the peak signal-to-noise ratio reaches 1.99%. Thus， the proposed method can effectively improve the quality of the reconstructed LF.