# sRrsR-Net: A New Low-Light Image Enhancement Network via Raw Image Reconstruction
## 4 Experiments
### Ablation Study  
To assess the individual impacts of the three modules RGB-iRGB, RAWFormer, and RRAW-sRGB on our low-light image enhancement model, seven ablation experiments were conducted on the LOL-v1 dataset. The baseline model is established without these three \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Type** & **Methods** & **FLOPs (G)** & **LOL-v1** & **LOL-v2-Real** & **LOL-v2-Synthetic** & **SID** \\ \hline \multirow{3}{*}{Transformer} & Restormer [20] & 144.25 & 0.20 & 0.25 & 0.30 & 0.28 \\  & Retinexformer [9] & 11.33 & **0.11** & 0.15 & 0.20 & 0.18 \\  & UFormer [41] & 15.85 & 0.15 & 0.20 & 0.25 & 0.22 \\ \hline \multirow{3}{*}{CNN} & RetinexNet [35] & 587.46 & 0.28 & 0.30 & 0.30 & 0.30 \\  & KinD [50] & 35.01 & 0.26 & 0.28 & 0.27 & 0.26 \\ \hline \multirow{3}{*}{U-Net-like} & LEDNet [54] & 35.90 & 0.19 & 0.22 & 0.23 & 0.21 \\  & Zero-DCE [16] & **4.81** & 0.12 & **0.12** & **0.13** & **0.12** \\  & EnlightenGAN [40] & 526.23 & 0.25 & 0.26 & 0.27 & 0.25 \\ \hline \multirow{3}{*}{Mixed} & Average & 170.11 & 0.19 & 0.22 & 0.25 & 0.23 \\  & Ours & 40.95 & 0.18 & 0.21 & 0.24 & 0.22 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Compares the runtime (in seconds) and computational complexity (FLOPs) of the four datasets. The best results are in bold. Figure 9: Comparison of running times across different datasets. The left side compares the average running times of other methods, while the right side shows our method’s running time compared to other state-of-the-art methods. modules but keeps the U-Nets unchanged. As for the other models in Table 5, when the RGB-iRGB or RRAW-sRGB module are not used, it means that just the U-Nets in these two modules are kept unchanged. Table 5 presents the quantitative results of these ablation experiments, and, qualitatively, Figure 10 gives the visual results of these experiments. Firstly, compared with the baseline model, there exist notable improvements in PSNR, SSIM, and LPIPS metrics on models **A**, **B**, and **C**, with only one module {RGB-iRGB, RAWFormer, or RRAW-sRGB}, especially for the PSNR metric. Concretely, with the RGB-iRGB module added, model **A** resulted in notable improvements in the PSNR, SSIM, and LPIPS metrics by 5.91 dB, 0.048, and 0.046, respectively, over the baseline model; model **B** resulted in notable improvements in the PSNR, SSIM, and LPIPS metrics by 5.31 dB, 0.04, and 0.048, respectively; model **C  
and LPIPS metrics by 6.45 dB, 0.06, and 0.095, respectively. Obviously, among these three modules, model **C** with just the RRAW-sRGB module achieved the best results with respect to all three metrics. Secondly, as illustrated in Table 5, when combining RGB-iRGB and RRAW-sRGB, or combining RAWFormer and RRAW-sRGB, the experiments in the corresponding models **D** and **E** achieved better results in any metric than the models **A**, **B**, and **C** with only one module, except in the SSIM metric for model **E**. For instance, compared with model **C**, model **D** has an improvement of 1.62 dB in PSNR, about 0.008 in SSIM, and 0.027 in LPIPS. Lastly, when combing all three modules, model **E** achieved the best result in all three metrics. Specifically, compared with model **D**, model **F** exhibits further improvement, about +0.89 dB in PSNR, +0.002 in SSIM, and \(-\)0.007 in LPIPS, respectively. According to the above quantitative analysis, compared with the baseline model, each module [RGB-iRGB, RAWFormer, and RRAW-sRGB] can help improve the model performance for low-light images. Moreover, combining these modules can achieve better results. As illustrated in Figure 10, just with the ISP blocks in the enhancement process, model **A**'s output images provide a more realistic color representation than the baseline model. With the RRAWFormer module, model **B** exhibits fewer blurry artifacts compared to the baseline, and its color tones are more consistent with real-world scenes. For instance, in the enlarged section of the red rope shown in Figure 10, the color closely resembles the reference image.