# Virtual View Synthesis Based on Asymmetric Bidirectional DIBR for 3D Video and Free Viewpoint Video
## 1 Introduction
Since no pixels are warped to these regions, large holes appear in the virtual image, called disocclusions [11]. Moreover, there is another type of hole known as the out-of-field region (OFR). This appears because the virtual view exceeds the capture range of reference view, resulting the region with no information  
Figure 1: Illustration of the three-dimensional (3D) warping. on the edge of virtual image. Therefore, artifacts handling hole filling in particular are a key issue for view synthesis. Generally, the hole-filling methods can be divided into two categories. The first is to preprocess the depth image by introducing a low-pass filter to reduce the hole size. The generation of disocclusion is related to the depth discontinuity between the foreground and the background. Large depth discontinuity usually causes a large disocclusion. [PERSON] et al. [12] use a symmetric Gaussian filter to smooth the depth image, aiming to reduce the depth discontinuity on the foreground edge and remove isolated noise pixels. However, this method produces a rubber plate effect, which appears as an uneven enlargement of the object. An asymmetric Gaussian filter is proposed in [13] to overcome this problem and give stronger smoothness to depth discontinuity in a vertical direction. However, the regions that do not produce disocclusion are also smoothed, causing some distortion in the virtual image and reducing the visual quality of these regions. In this case, an edge-based smoothing filter is proposed to preprocess the foreground edge only [14]. [PERSON] et al. [15] implement preprocessing in the transformed domain by applying a structure-aided filter. An adaptive filter can prevent the generation of hole or decrease hole size to some extent. The depth image-smoothing methods are suitable for small baseline configurations. They are hardly used in the large baseline situation. Moreover, OFRs are not caused by depth discontinuities, so they would not be prevented by the smoothing process. The other type of method is to fill the holes by using the texture correlation of surrounding pixels. Inpainting-based methods are effective solutions to fill the unknown regions, such as [PERSON]'s exemplar-based inpainting algorithm [16]. In this method, the filling priority is first computed based on the texture distribution of surrounding valid pixels, and then the best matching patch in the source region is searched and copied to the hole region. It can produce plausible results without introducing blurring effects. However, for disocclusion filling, as the exposed regions belong to the background, they should be filled with background texture. Directly applying the [PERSON]'s method would cause some foreground textures to be sampled to fill the holes, resulting in foreground blending. To overcome this drawback, some methods optimize the inpainting process by introducing the depth features. In [17], the depth term is added in priority computation to give the patch with lower depth variance a higher priority, and depth weight is considered when searching for the best matching patch. However, this method requires the known depth image of virtual view, which is unrealistic in practical applications. [PERSON] et al. [18] synthesizes the virtual depth image in 3D warping, thereby providing depth information for the subsequent inpainting process. But when the depth value of foreground edge is inaccurate, ghosts would affect the hole-filling quality. A depth-based gray-level distance matching cost computation method is proposed in [19], but some artifacts might be produced  
Figure 2: Schematic diagram of artifact generation. due to the depth errors. In order to prevent the interference of foreground texture, some foreground segmentation methods are proposed [20; 21; 22]. The quality of the synthesized image through these methods is strongly dependent on the accuracy of foreground segmentation. This is a challenging task in some situations, such as the existence of multiple depth layers. Sometimes the seed points need to be manually identified.