The light field imaging technology can realize the application of the full-focus image synthesis of the scene and the de-occlusion reconstruction of background target through the classification of the light field information of the scene. How to effectively evaluate the focus area in the image is a prerequisite for the above application. The dispersion characteristics of the defocusing point of a conventional imaging system are fundamentally different from those of the defocusing area in the refocusing image of the light field. Therefore, the evaluation criteria based on the diffusion characteristics of the defocusing point cannot be applied to the evaluation of the focus of the refocusing image of the light field. Aiming at the above problems, in this paper, starting from the principle of refocusing of light field imaging, we analyze the blurring characteristics of the defocused target image, and propose a new evaluation function of the focus of the refocusing image of the light field. Based on this, the refinement segmentation method of the focal region is studied to achieve the final focus area extraction. According to the indoor scene data set captured by the camera array of Stanford university, in this paper we use the traditional focus degree evaluation algorithm and the algorithm to evaluate the focusing degree of the foreground target potted plant in the scene and obtain the complete information about the foreground target, therefore we also study the refined segmentation algorithm. Then, in the process of refocusing the background object (CD box), the foreground light is screened out, and the reconstructed image of the specified focusing plane is obtained. Using the peak-signal-to-noise ratio and mean structural similarity index measure to evaluate the quality of the target in refocusing area, the results show that the proposed algorithm in this paper can effectively mark and separate the imaginary artifact information and ensure the high-quality focus reconstruction of the partially occluded target in the scene, which can effectively overcome the influence of the edge and texture information of the object in the scene on the defocusing area. The method presented in this work has better adaptability to the focus degree evaluation of the refocusing image of the light field.