Endoscopic image depth estimation is an important technical challenge in minimally invasive surgery. In order to improve the accuracy of depth estimation of endoscopic image, an endoscopic image depth estimation method based on improved Monodepth2 was proposed. In the depth estimation network, the encoder used the ResNet34 module and introduced the sparse attentive backtracking (SAB) attention mechanism, the improved feature pyramid network (FPN) module and feature enhancement module, so that the proposed network could better understand the global information, deal with multi-scale features flexibly and effectively, and further enhanced its stability and reliability. The decoder obtained the depth information and pose information of the image through up-sampling. To further improve the accuracy of the proposed method, photometric reprojection error, structural similarity and edge perception smoothing error were used as loss functions. The evaluation used Hamlyn public dataset, and the experimental results show that the proposed method can estimate the depth information of endoscope image more accurately, which further verifies the effectiveness and accuracy of the proposed method.