## 3 Results
### Results on the Visual Experiment  
Visual scores were collected from eight observers. For each of the 30 samples, observers assessed the color reproduction quality of digital color visualization by visually comparing the digital reproduction obtained with sRGB and the CAAD. In order to be able to analyze observer repeatability and reproducibility, the same test was repeated by each observer three times, each of the sessions being planned on different days. This resulted in a total of 720 visual scores for the color representation calculated with sRGB color space, 720 corresponding visual scores for the color representation by CAAD, and 720 preferences for color representation by either sRGB color space or CAAD model. To statistically validate the experiment, an analysis of variance (ANOVA) was conducted. ANOVA is a statistical technique used to assess whether there are significant differences between the means of multiple groups by examining the contribution of different sources of variability to the total observed variance. Prior to the ANOVA, a preliminary analysis of the data was performed to verify that the underlying assumptions were reasonably satisfied. The normality assumption was found to be acceptable, and no evident heteroscedasticity was detected. In this case, the ANOVA was used to evaluate the statistical significance of each factor that might influence the assigned scores. The results are summarized in Table 6.  
The method used to render the color samples (sRGB or CAAD) accounts for nearly all of the variability in the data, as indicated by its exceptionally high F-value and extremely small _p_-value. This suggests that the difference between the sRGB and CAAD methods is the primary source of variation in the scores. Although the differences between observers are statistically significant, they contribute less to the overall variability, reflecting individual differences among participants, but with a smaller effect size. Similarly, the session factor is significant, but its influence is relatively minor, likely due to learning or fatigue effects over time. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Source** & **F** & _p_**-Value** \\ \hline Method & 4096.09 & \(<\)10\({}^{-24}\) \\ \hline Observer & 18.15 & \(\approx\)3.1 \(\times\) 10\({}^{-23}\) \\ \hline Session & 8.90 & \(\approx\)1.4 \(\times\) 10\({}^{-4}\) \\ \hline Method x Observer & 19.05 & \(\approx\)2.0 \(\times\) 10\({}^{-24}\) \\ \hline Observer x Session & 2.95 & \(\approx\)1.9 \(\times\) 10\({}^{-4}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 6: ANOVA results for sources of variability in the visual experiment. \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & & **sRGB** & \multicolumn{2}{c}{**MDCIM iPhone XS**} & \multirow{2}{*}{**CAAD**} \\ \cline{3-4}  & \(\gamma\) & 2.4 & 2.255 & 2.314 \\  & \(d_{0}\) & 0.04045 & 0.00784 & 0.00849 \\ \(G\) & \(k_{1}\) & 0.947867 & 0.99026 & 0.988967 \\  & \(k_{2}\) & 0.055 & 0.00974 & 0.011033 \\  & \(\beta\) & 0.077399 & 0.01394 & 0.012899 \\ \hline \multirow{4}{*}{\(B\)} & \(\gamma\) & 2.4 & 2.287 & 2.34 \\  & \(d_{0}\) & 0.04045 & 0.00784 & 0.00951 \\ \(k_{1}\) & 0.947867 & 0.99001 & 0.987417 \\ \cline{1-1}  & \(k_{2}\) & 0.055 & 0.00999 & 0.012583 \\ \cline{1-1}  & \(\beta\) & 0.077399 & 0.01264 & 0.013863 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: _Cont._The significant interaction between method and observer suggests that some participants perceive one method as more effective than the other, while others do not notice such a clear difference. The interaction between method and session is also significant, though weaker, indicating that preferences for one method over another may slightly vary across sessions, but the effect is less pronounced. A visual comparison of the score distributions through a boxplot further reinforces the statistical findings. The boxplot in Figure 6 clearly illustrates that the CAAD model consistently received higher ratings than the sRGB method.