## 4 Experiment and Security Analysis
### Image Quality Analysis  
In this subsection, we adopt ENIQA [35] and BRISQUE [36] to evaluate the image quality of the stego image, \(I^{\prime\prime}_{ouct}\), generated in Phase-1. ENIQA is a high-performance, general-purpose, no-reference assessment method based on image entropy. The range of the ENIQA score is within [0, 1]; a lower score represents higher quality. BRISQU is another high-performance, general-purpose, no-reference assessment method based on the Natural Scene Statistics (NSS) extraction and the feature vectors calculation. The BRISQUE score is usually in the range [0, 100]; smaller scores reflect better perceptual quality of the test image with respect to the input model. Table 9 shows the ENIQA and BRISQUE scores for the source, target, and the stego image, \(I^{\prime\prime}_{ouct}\), where its colors are borrowed from those in the source and target images. using an optimal weight vector. The average ENIQA scores is 0.0975, which is close to 0, while the average BRISQUE score is 13.9201, which is far from the worse scores, 100. Both scores reflect that our scheme can produce a stego weighted color-transferred image that exhibits good image quality. Figures 5-10 show the visual inspection of six test images along with the optimal weighted vectors, W*. We exhibit the source, target image, the stego optimal weighted color transferred image, \(I^{\prime\prime}_{ouct}\), and the final dual stego images: \(I^{\prime\prime}_{s1}\) and \(I^{\prime\prime}_{s2}\). Table 10 exhibits the results of the full-reference image quality assessment, where we consider the optimal weighted color-transferred image, \(I^{\prime\prime}_{ouct}\), as the reference image and the dual stego images, \(I^{\prime\prime}_{s1}\) and \(I^{\prime\prime}_{s2}\), as the test images. We list the other metrics of the full-reference image quality assessment in Table 11. Specifically, we report the following standard metrics to evaluate the image quality: Mean Square Error, Peak Signal Noise Ratio (PSNR) [37], Visual Saliency-induced Index (VSI) [38], Structural Similarity Index (SSIM) [39], Information Content Weighting Mean Squared Error (IW-MSE) [40], University Image Quality Index (Q-Index) [41; 42]. In metrics introduced by [38; 39; 41], scores are within the range [0, 1]; the score close to 1.0 represents that the test image has less distortion in comparison with the reference image. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**No.** & **Source** & **Target** & **Resolutions.** & **W*(R, G, B)** & **(a)** & **(b)** & **(c)** & **(d)** & **(e)** \\ \hline
1 & Baboon & Barbara & 512 \(\times\) 512 & (0.45, 0.48, 0.50) & 9.554 & 0.318 & 0.126 & 0.039 & 0.02 \\
2 & Lena & Goldhill & 512 \(\times\) 512 & (0.48, 0.60, 0.42) & 9.523 & 0.298 & 0.125 & 0.053 & 0.02 \\
3 & Pepper & Boats & 512 \(\times\) 512 & (0.47, 0.54, 0.48) & 9.352 & 0.317 & 0.119 & 0.035 & 0.018 \\
4 & Kodim07 & Kodim24 & 512 \(\times\) 768 & (0.48, 0.46, 0.48) & 14.235 & 0.516 & 0.203 & 0.066 & 0.03 \\
5 & Kodim20 & Kodim22 & 512 \(\times\) 768 & (0.57, 0.59, 0.58) & 13.933 & 0.454 & 0.187 & 0.056 & 0.03 \\
6 & Kodim23 & Kodim11 & 512 \(\times\) 768 & (0.54, 0.49, 0.54) & 13.616 & 0.445 & 0.191 & 0.07 & 0.032 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: The timing results of six test images.