## 2 Related Work
The foreground objects are removed from the reference image and depth image, and then the removed regions are filled by a modified [PERSON]'s inpainting algorithm. The constructed background image is applied to fill the disocclusions in the virtual image. [PERSON] et al. [PERSON] et al. (2018) use foreground object extraction to segment the reference image into multiple layers. Global disparity adjustments and local depth control are performed in each layer so that the visual discomfort is alleviated. However, accurate separation of foreground and background objects is difficult, especially for the situation that the foreground and background contain multiple depth levels. Furthermore, the OFRs are not all belong to backgrounds and should not be filled by the same priority computation as the dis-occluded regions. The other type of methods is to handle the disocclusion in temporal domain. For 3D video and FVV, the region occluded by the foreground objects in the current frame may become visible in other frames [PERSON] et al. (2018); [PERSON] et al. (2018). [PERSON] et al. [PERSON] et al. (2018) propose an online background model construction method based on switchable Gaussian model (SGM), which improves the adaptability to the scene. [PERSON] et al. [PERSON] et al. (2018) establish an adaptive background model based on the Gaussian mixture model (GMM) to fill the dis-occluded regions. However, for a single reference image and still foreground objects, the occluded backgrounds in the scene may not be fully obtained, so it is difficult to establish a good background model in these situations. Furthermore, when virtual view is generated using multiple reference views, view blending is an effective method to filling the disocclusions [25; 26; 27]. [PERSON] et al. [28] point out that using two or more neighboring reference views can greatly reduce the holes in the virtual view. This is because the background region, which is not visible in the left reference view may be visible in the right reference view, so the hole-filling results can be very accurate. [PERSON] et al. [24] also use two reference views in their method, and obtain the virtual view through a weighted view blending process. However, multi-view rendering requires more devices and transmission bandwidth compared to single view rendering. In Reference [29], a real-time DIBR system that consists of disparity estimation and view synthesis is proposed. It applies different methods to handle the holes for view interpolation and extrapolation. Moreover, the system is implemented on FPGA to achieve a high processing speed. In order to reduce the computational cost, holes in the OFRs are considered as background regions in the filling process. For the virtual view outside the baseline, view blending can only reduce a limited number of holes. Therefore, the research on single view rendering method is still required. In this paper, a single reference image and its depth image are used for the synthesis of virtual image. We apply different methods to handling the artifacts based on their natures. The OFRs are filled with the extended reference image and depth image. This process will focus on maintaining the local consistency of the texture rather than just filling the holes with background pixels. Ghosts are removed in the depth image preprocessing and mapped to the correct position. In the modified 3D warping process, cracks are filled and all pixels in the virtual image maintain the proper occlusion relationship. Disoccluded regions are filled from the local background side first. The source regions are not only limited to the virtual image, but also contain the regions which have similar depth values in the reference image. Since an image contains different edge structures and texture features, an adaptive patch size based on gradient information is applied to the image inpainting approach.