Aiming at the problems of incomplete detection targets and blurred edges in light field image saliency detection, this paper proposes an edge-guided light field image saliency detection method. The edge enhancement network is used to extract the main image and edge enhancement image of all-focus image, and the initial saliency map is obtained by combining the features extracted from the main image and focal stack image to improve the accuracy and completeness of detection results. The initial saliency map and edge enhancement further learns the information of edge characteristics and highlights the edge details through the feature fusion module. Finally, the boundary mixing loss function is used to optimize the saliency map with clearer boundaries. The experimental results show that on the latest light field data set, F-measure and MAE are 0.88 and 0.046 respectively, which are better than the existing RGB images, RGB-D images and light field image saliency detection algorithms. The proposed method can more accurately detect complete salient objects from complex scenes, and obtain saliency maps with clear edges.