# Edge-Guided Dual-Stream U-Net for Secure Image Steganography
## 4 Experiments
### Model Complexity Analysis  
In terms of model complexity analysis, we compared the proposed method with other steganographic algorithms, as summarized in Table 7. Regarding computational complexity, our method requires 330.353 FLOPs, which is significantly higher than SteganoGAN and FNNS but 19% lower than LISO (408.770 GFLOPs). For parameter count, our model utilizes 2.502M parameters, exceeding those of comparative methods, primarily due to the adoption of a more complex network architecture to enhance steganography performance. In processing speed, our method achieves an average of 0.4594 s per image, outperforming LISO (0.5993 s/img) but lagging behind SteganoGAN and FNNS. Overall, while our approach demands relatively higher computational resources, it achieves superior steganographic performance through moderate computational overhead, demonstrating a favorable performance trade-off in practical applications. \begin{table}
\begin{tabular}{c c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Method**} & \multicolumn{6}{c}{**Error Rate (\%)**} & \multicolumn{6}{c}{**PSNR**} & \multicolumn{6}{c}{**SSIM**} \\ \cline{2-13}  & **1 bit** & **2 bit** & **3 bit** & **4 bit** & **1 bit** & **2 bit** & **3 bit** & **4 bit** & **1 bit** & **2 bit** & **3 bit** & **4 bit** \\ \hline SteganoGAN [17] & 0.8153 & 0.8128 & 0.8184 & 0.8197 & 0.8843 & 0.8532 & 0.8516 & 0.8429 & 0.8736 & 0.8902 & 0.8419 & 0.8147 \\ FNNS-R [31] & 0.9452 & 0.8821 & 0.8164 & 0.8026 & 0.9728 & 0.9254 & 0.8831 & 0.8285 & 0.9801 & 0.9375 & 0.8973 & 0.8216 \\ FNNS-D [31] & 0.8172 & 0.7355 & 0.5632 & 0.6723 & 0.9950 & 0.9776 & 0.8042 & 0.9537 & 0.9446 & 0.9477 & 0.9443 & 0.9243 \\ FNNS-DE [31] & 0.6124 & 0.5468 & 0.4089 & 0.6145 & 0.8652 & 0.8380 & 0.7315 & 0.7372 & 0.7128 & 0.6854 & 0.6432 & 0.6381 \\ LISO [19] & 0.9925 & 0.9836 & 0.9742 & 0.9427 & 0.9949 & 0.9912 & 0.9680 & 0.8815 & 0.9952 & 0.9894 & 0.9794 & 0.9678 \\ Ours & 0.9949 & 0.9947 & 0.9760 & 0.9627 & 0.9981 & 0.9972 & 0.9970 & 0.9892 & 0.9965 & 0.9904 & 0.9903 & 0.9836 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Comparison of FSIM performance of different steganographic methods under multi-load conditions. \begin{table}
\begin{tabular}{c c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Method**} & \multicolumn{6}{c}{**Error Rate (\%)**} & \multicolumn{6}{c}{**PSNR**} & \multicolumn{6}{c}{**SSIM**} \\ \cline{2-13}  & **1 bit** & **2 bit** & **3 bit** & **4 bit** & **1 bit** & **2 bit** & **3 bit** & **4 bit** & **1 bit** & **2 bit** & **3 bit** & **4 bit** \\ \hline SteganoGAN [17] & 3.40 & 6.29 & 11.13 & 15.70 & 25.32 & 24.27 & 25.01 & 24.94 & 0.84 & 0.82 & 0.82 & 0.82 \\ FNNS-R [31] & 0.04 & 0.32 & 2.16 & 10.38 & 34.68 & 30.79 & 29.32 & 28.22 & 0.91 & 0.84 & 0.79 & 0.74 \\ FNNS-D [31] & 0.00 & 0.00 & 0.00 & 13.65 & 37.94 & 34.51 & 27.77 & 34.78 & 0.95 & 0.90 & 0.72 & 0.89 \\ FNNS-DE [31] & 0.00 & 0.00 & 0.00 & 1.74 & 25.25 & 22.35 & 21.02 & 21.33 & 0.77 & 0.74 & 0.62 & 0.64 \\ LISO [19] & 2 \(\times\) 10\({}^{-4}\) & \(5\times 10^{-4}\) & \(3\times 10^{-3}\) & \(4\times 10^{-2}\) & 33.83 & 32.70 & 29.78 & 25.46 & 0.90 & 0.89 & 0.75 & 0.68 \\ Ours & 0.00 & 0.00 & 0.00 & 0.03 & 37.88 & 35.89 & 30.99 & 27.72 & 0.95 & 0.91 & 0.81 & 0.79 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Comparison with other state-of-the-art steganography algorithms with different payloads on MS-COCO dataset.