The real captured dataset of LOL contains 500 low/normallight image pairs. Most low-light images are collected by changing exposure time and ISO, while other configurations of the cameras are fixed. We capture images from a variety of scenes, e.g., houses, campuses, clubs, streets.

Since camera shaking, object movement, and lightness changing may cause misalignment between the image pairs, inspired by [41], a three-step shooting strategy is used to eliminate such misalignments between the image pairs in our dataset. For one scene, we first shoot two normal-light images $N_1$ and $N_2$. Then, we change the exposure time and ISO to capture a series of low-light images. Finally, we set the exposure time and ISO back to shoot another two normal-light images $N_3$ and $N_4$. The average of $N_i (i = 1,2,3,4)$ is treated as the ground-truth $G=\frac{1}{4}\sum^4_{i=1}N_i$. Then, we check whether there is object or camera movement. Specifically, the misalignment for these normal-light images is measured by $M=\frac{1}{4}\sum^4_{i=1}MSE(Ni, G)$. If M > 0.1, we abandon the corresponding pair.

These raw images are resized to 400 × 600 and converted to Portable Network Graphics format. The dataset is publicly available.