# High-Precision Depth Map Estimation from Missing Viewpoints for 360-Degree Digital Holography
## 5 Discussion and Conclusions
The limitations of the proposed model covered in this study are the minute residual images near the border area of each object and the weak background noise in the estimated depth maps. To overcome these issues, one needs to find approaches to place relatively large weights on these border areas and then enhance precision estimations of these areas. It is also worth mentioning that the image resolution and extraction speed of deep learning-based depth maps can be improved by adjusting the model's parameters, such as filters and filter sizes, and then optimizing the ratio of training/testing data. Moreover, we note that only the diffraction efficiency element, that is, the direct observation of the reconstructed holographic 3D image, was used as a comparative measure for the quality of the H3D image in this study. We plan to supplement this measure through further analysis, considering parameters such as the contrast ratio of intensity, clearness, and distortion to evaluate H3D images. We plan a future study to optimize the interval of missing viewpoints. Currently, without the standard appropriate for missing viewpoints, situations in various viewpoints have been used to generate 360-degree holographic video content. Future studies to optimize the interval of missing viewpoints are expected to contribute to AR, VR, and holographic metaverse applications, leading to a low computational-cost method in providing realistic 360-degree holographic content. The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/app12199432/s1](https://www.mdpi.com/article/10.3390/app12199432/s1)]([https://www.mdpi.com/article/10.3390/app12199432/s1](https://www.mdpi.com/article/10.3390/app12199432/s1)), Figure S1: PSNR trend with respect to loss function (MSE-SSIM) coefficient; Figure S2: Results of CGH reconstruction for cube, cone, and sphere; Figure S3: Depth map estimation result comparison for cube, cone, and sphere; Figure S4: Numerical CGH reconstruction result comparison for cube, cone, and sphere; Figure S5: ACC trend of CGHs generated using the estimated depth map of each model to the observer's rotation angles for objects; Figure S6: Depth map estimation comparison to ground truth depth map for a typical section where two objects overlap; Figure S7: CGH's reconstruction results for a typical section where two objects overlap; Figure S8: Depth map estimation results for dodecahedron, which is not used in the course of the training phase; Figure S9: Holographic 3D reconstruction from CGH for objects not used in the course of training phase to confirm the accommodation effect; Figure S10: ACC trend of CGHs generated using the depth map estimated from each model to the observation's rotation angle for the shape of a dodecahedron; Figure S11: Depth map estimation comparison with respect to ground truth depth map in a typical section where two objects overlap with the solid shape of dodecahedron which is not used in the course of the training phase; Figure S12: CGH's reconstruction results in a typical section where two objects overlap with the solid shapes of dodecahedron, which is not used in the course of the training phase; Video S1: Results of numerical CGH reconstruction for entire viewpoints; Video S2: Result of optical CGH reconstruction for entire viewpoints. Conceptualization, H.K., M.Y. and C.K. ; methodology, H.K., M.Y. and C.K. ; software, H.K., H.L. and M.J.; validation, H.K., M.Y. and C.K. ; formal analysis, H.K., H.L. and M.J.; investigation, H.K., H.L. and M.J.; resources, H.K. and Y.L. ; data curation, H.K. and Y.L. ; writing--original draft preparation, H.K., H.L. and M.J.; writing--review and editing, H.K., M.J. and M.Y. ; visualization, H.K. ; supervision, M.Y. and C.K. ; project administration, M.Y. and C.K. ; funding acquisition, M.Y. and C.K. All authors have read and agreed to the published version of the manuscript. This research was funded by the Ministry of Science and ICT (MSIT, South Korea) grant number V0408-20-1001. The APC was funded by authors. Not applicable.