# Self-Guided Pixel-Wise Calibration for Low-Light Image Enhancement
## 4 Experiment
### Ablation Study  
#### 4.5.1 Contribution of Each Module  
Several ablation experiments are carried out to thoroughly evaluate the efficiency of the components introduced in Section 3. These tests systematically assess the contributions of the PGF, CCM, and \(\mathcal{L}_{exp}\) regarding the technique's performance. To achieve this objective, each component is removed separately and experiments are designed accordingly. In the case of w/o \(\mathcal{L}_{exp}\), the model is trained using a single exposure value instead of excluding the entire \(\mathcal{L}_{exp}\).  
As depicted in Figure 5, the first column shows low-light input images, whereas the fifth column displays enhanced images using SGPC, effectively demonstrating the enhancing impact of our proposed strategy. The outcomes of removing one component at a time are shown in the other three columns. The enhanced image after removing the PGF (refer to the second column) exhibits significant noise in the wooden frame of the bookshelf in the upper image and the wall in the lower image. This seriously impacts the inner characteristics of the image. The incorporation of PGF successfully preserves image texture features while effectively reducing noise. Furthermore, the third column denotes that the absence of CCM leads to reduced color contrast in the enhanced output, making the images appear as if they are covered with a veil. However, the rose looks much more vivid and stunning when CCM is included. Finally, the significant difference between the images in the fourth and fifth columns makes it clear that, in the absence of the \(\mathcal{L}_{exp}\) restriction, the originally brighter regions in the low-light image act as locally overexposed after enhancement. Examples of such findings deviate from expectations, as proven in the case of the cup in the lower image.  
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Method**} & \multirow{2}{*}{**Type**} & \multicolumn{3}{c}{**NIQE \(\downarrow\)**} & \multicolumn{3}{c}{**NR-CDIQA \(\uparrow\)**} & \multicolumn{3}{c}{**PSNR \(\uparrow\)**} & \multicolumn{3}{c}{**SSIM \(\uparrow\)**} \\ \cline{3-11}  & & **MEF** & **LIME** & **DICM** & **MEF** & **LIME** & **DICM** & **LOL** & **SICE** & **LOL** & **SICE** \\ \hline Retinex\(\mathrm{DIP}\)[34] & S & 3.2494 & 3.6828 & 3.2724 & 2.9536 & 2.8389 & 3.0863 & 13.3952 & 15.5559 & 0.6717 & 0.5528 \\ RetinexNet [35] & S & 4.9043 & 4.9093 & 4.3144 & 3.0434 & 2.9908 & 3.0372 & 19.3847 & 17.8776 & 0.5816 & 0.5397 \\ DRBN [36] & S & 3.6213 & 3.8659 & 3.1589 & 3.0866 & 3.0626 & 3.0488 & 18.8061 & 18.5685 & **0.8314** & 0.5760 \\ \hline Zero-DCE [20] & U & 3.3085 & 3.7859 & 3.0972 & 3.0782 & 3.0123 & 3.0122 & 16.7555 & 18.2762 & 0.7345 & 0.5810 \\ RUAS [18] & U & 4.0820 & 4.2610 & 4.7042 & 2.6383 & 2.9542 & 2.3145 & 18.4507 & 12.5187 & 0.7696 & 0.5260 \\ SCI [19] & U & 3.4322 & 4.1394 & 3.6135 & 3.0023 & 3.1086 & 2.5637 & 16.4467 & 15.0204 & 0.7094 & 0.5739 \\ PairLIE [17] & U & 4.1720 & 4.2791 & 4.1086 & 3.1371 & 3.0526 & 2.9802 & 19.0792 & 19.5461 & 0.8134 & **0.5904** \\ SGPC (Ours) & U & **3.0588** & **3.6475** & **2.9183** & **3.2551** & **3.1993** & **3.1345** & **20.0836** & **19.7556** & 0.7901 & 0.5833 \\ \hline \hline \end{tabular}
\end{table}
Table 1: _Cont._  
Figure 5: Visual comparison from the ablation study of the contribution of each module (spatial PGF, CCM, and \(\mathcal{L}_{exp}\)). The final column illustrates the enhancement results achieved by our method. Certainly, w/o \(\mathcal{L}_{exp}\) refers to training with a single exposure value, rather than excluding the entire \(\mathcal{L}_{exp}\). Please zoom in to see the details.