# Quality Assessment of 2.5D Prints Using 2D Image Quality Metrics
## 4 Results and Discussion
### Can We Obtain Insights on 2.5D Prints' Quality from 2D IQMs?
#### 4.2.3 Printer Mode Set  
In both set-up captures, iCID's lightness difference map detected more differences on the surface of the elevated parts and on the background in both Alto and Brila mode prints in the three images. iCID's lightness contrast and lightness structure maps found more differences on the surface of the elevated parts in both prints in the flower and snowflake images. CIEDE2000 and SCIELAB detected more color differences on the edges in the Alto mode print and on the surface of the elevated part in the Brila mode print in the flower image (Figure 12). This is expected because the Brila mode introduces color shift. In addition, the Alto mode has higher elevation compared to the Brila mode. Therefore, more color differences are located on the edges in the Alto mode print. CIEDE2000, SCIELAB, and iCID's lightness structure map found more differences in the three images' both prints in the MS captures than in the SS ones.  
Figure 10: Example of fine details detection from surface roughness print of the wood image by SCIELAB in captures from the MS (**left**) and the SS (**right**). The images were cropped for illustration purpose. Zero means that there is no difference.  
Figure 9: Example of more difference detection in print with surface roughness by iCID’s lightness structure map in the MS captures in the wood image. Zero means there is no difference while one means that there is more difference. The images were cropped for illustration purpose. The mean quality maps are given on top while registered 2.5D print captures of the MS at elevation angle = \(30^{\circ}\) and azimuth angle = \(-20^{\circ}\) are given on bottom.  
To conclude, the quality maps of the tested IQMs are informative regarding 2.5D prints' QA. More specifically, they are informative in a similar way regarding difference detection on areas such as edges, elevated parts' surfaces, and background. For future work, it will be interesting to investigate quality maps along with height maps.  
All differences detected by the tested IQMs (mainly on the edges, on the surface of the elevated parts, and on the background) for the examined set of images are consistent with the observers' feedback (mainly on elevation and aspects introduced by elevation (e.g., shadow)). This is better visible in the MS captures. As a result, this shows that the  
Figure 11: iCID’s lightness structure (mean) quality maps from the MS (**top**) and the SS (**bottom**) captures. It detected more differences on the edges in the 1 mm maximum height print compared to other two prints in both set-up captures. The maps were cropped for illustration purpose. Zero means there is no difference.  
Figure 12: SCIELAB’s mean quality maps of the flower image for the Alto mode (**left**) and the Brila mode (**right**) prints from the MS captures. The maps were cropped for illustration purpose. Zero means there is no difference.  
mentioned IQMs can be used for QA of 2.5D prints for specific attributes/features with a specific capture set-up.