# High-Precision Depth Map Estimation from Missing Viewpoints for 360-Degree Digital Holography
## 4 Experiment Results and Discussion
### Qualitative Results of the Image Quality
The data set for RGB color image and ground truth depth map was created using Autodesk Maya 2018, Maya Software ([[https://www.autodesk.com/products/maya/overview](https://www.autodesk.com/products/maya/overview)]([https://www.autodesk.com/products/maya/overview](https://www.autodesk.com/products/maya/overview)), accessed on 17 September 2022). \[H(x,y)=L_{1}(x,y)e^{i0}+L_{2}(x,y)e^{i\pi/2}+L_{3}(x,y)e^{i\pi}+L_{4}(x,y)e^{i3 \pi/2} \tag{2}\]8 ACC trend of CGHs generated using the depth map estimated from each model to the observation’s rotation angle for the shape of an icosahedron. The \(x\)-axis represents the observation’s rotation angle and the \(y\)-axis represents the \(ACC\) of CGH synthesized from each model. Gray-colored boxes indicate regions where two objects overlap for each 360-degree video scene. (Results of the dodecahedron can be seen in Figure S10). 4.2.4 Further Comparison of the Proposed Model (HDD) with Previous Models (Using Complicated Object)  
We present a further experiment of depth map estimation performed using more complicated objects that are not used in the course of the training phase so that we can demonstrate the superiority of the proposed model (HDD) over AdaBins and CDD in applications for 360-degree digital holographic content. We synthesized CGH with the estimated depth map and then reconstructed a holographic 3D image to compare the depth map estimation performance of the proposed model with the performance of previous models. For this experiment, we chose an amorphous rock, which is as complicated as the level of real objects. Since Section 4.2.4 is part of additional experiments, the data used in this section were not included in the total number of data--9832 images--mentioned in this paper. The depth maps, as shown in Figure 16, were estimated under the same conditions as the weights of each model which had been obtained in the course of the training phase based on the four pre-existing objects (torus, cube, cone, and sphere). In Figure 16, although the approximate trends of HDD and CDD are similar, it can be visually confirmed that HDD is closer to the ground truth depth map compared to CDD. It can be visually confirmed that the AdaBins estimated objects to be brighter than the ground truth depth map. To compare the results of HDD with those of CDD, we calculated values of the _PSNR_ for an amorphous rock: the _PSNR_ of HDD was 27.65 dB, while the _PSNR_ of CDD was 26.27 dB. \[H(x,y)=L_{1}(x,y)e^{i0}+L_{2}(x,y)e^{i\pi/2}+L_{3}(x,y)e^{i\pi}+L_{4}(x,y)e^{i3 \pi/2} \tag{2}\]9 Depth map estimation results for a new scene which was composed of a pair of amorphous solid rocks. The red box indicates the result from the proposed model (HDD) in comparison with other models. The 3D model of each amorphous rock was provided from TurboSquid, [[https://www.turbosquid.com/ko/3d-models/cave-rock-02-base-model-1944210](https://www.turbosquid.com/ko/3d-models/cave-rock-02-base-model-1944210)]([https://www.turbosquid.com/ko/3d-models/cave-rock-02-base-model-1944210](https://www.turbosquid.com/ko/3d-models/cave-rock-02-base-model-1944210)), accessed on 17 September 2022). Data set for RGB color image and ground truth depth map for a pair of these solid objects was created using Autodesk Maya 2018, Maya Software ([[https://www.autodesk.com/products/maya/overview](https://www.autodesk.com/products/maya/overview)]([https://www.autodesk.com/products/maya/overview](https://www.autodesk.com/products/maya/overview)), accessed on 17 September 2022). Figure 4.0 Reconstruction results from CGHs in a typical section where two objects overlap, as seen in Figure 4.1 (The red box indicates the result from the proposed model. Results of the dodecahedron can be seen in Figure S12). The observational camera's focus was placed on the head of the target object between the two objects reconstructed from CGH, as marked with an arrow in Figure 4.2 Figure 17 shows the 3D images reconstructed from CGH for ground truth, HDD, AdaBins, and CDD.