# Enhancement of Low-Light Images Using Illumination Estimate and Local Steering Kernel
## 4 Simulation and Results
### Objective Evaluation  
To objectively evaluate the performance of the proposed method, a quantitative evaluation is conducted on the resulting images. The methods used for quantitative evaluation are LOE (lightness order error), peak signal-to-noise ratio (PSNR), and structural similarity (SSIM) [25]. LOE is proposed to objectively evaluate the naturalness of an image and evaluate the change in illumination of an image by assessing the sequential change in brightness of the image. Smaller LOE values indicate a more natural brightness transition in the resulting images. PSNR is the most commonly used video quality metric and is measured in (dB). PSNR evaluates the difference between two images, with higher values indicating greater similarity and less distortion between the images. SSIM compares the brightness, contrast, and structural similarity between two images, with values ranging from 0 to 1; values closer to 1 signify greater structural similarity. Tables 2-4 show the LOE, PSNR, and SSIM results for the processed videos in Section 4.2.  
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Image** & **Dark Light** & **LIME** & **RBMP** & **LIIEN** & **PM** \\ \hline LOL493 & 162.072 & 94.739 & 88.600 & 80.840 & 72.030 \\ LOL665 & 150.877 & 111.682 & 77.145 & 69.061 & 49.115 \\ LOL669 & 194.140 & 143.954 & 61.474 & 86.141 & 123.681 \\ LOL778 & 192.890 & 123.611 & 112.848 & 80.802 & 83.162 \\ LOL780 & 248.520 & 133.832 & 190.140 & 121.238 & 124.381 \\ \hline Average & 189.700 & 121.564 & 106.041 & 87.616 & 90.474 \\ \hline \end{tabular}
\end{table}
Table 2: LOE score comparison of test image.  
In the quantitative evaluation, dark light shows a poor performance overall, with a mean value of 189.700 for LOE and a mean of 14.847 and 0.488 for PSNR and SSIM, respectively. Overall, the quantitative evaluation is inadequate for the resulting videos from LIME; in particular, the PSNR average shows the lowest value at 14.167. While RBMP has superior PSNR and SSIM, the average LOE value is 106.041, which is slightly insufficient for the proposed algorithm. LIIEN has superior average LOE values, but PSNR and SSIM values show low average values. The quantitative evaluation of the proposed method shows that the average LOE value is 90.474, the average PSNR is 18.338 (dB), and the average SSIM is 0.576, which are generally superior to the existing methods. Tables 5-7 show the quantitative evaluation using 485 images from the LOL dataset, 100 images from the VE-LOL-L dataset, and 360 images from the SICE dataset for objective evaluation. Tables 5-7  
luminance changes in the resulting images. However, the results are similar to or slightly higher than the results of processing with RBMP and LIIEN.  
The PSNR comparison results in Table 6 show that the best results are processed by the proposed algorithm. In particular, the VE-LOL-L dataset shows improvements of 2.333 (dB), 2.518 (dB), 0.417 (dB), and 3.434 (dB) over the existing method, respectively, and the most similar results are shown for the control image.  
SSIM, the proposed method in Table 7, shows the highest value of 0.529 on the SICE dataset, with improvements of 0.100, 0.070, 0.024, and 0.069 over the existing methods, respectively. The SSIM results of the proposed method are superior to the existing methods in most cases, and they produce the most structurally similar results to the control image.