BVI-Lowlight-Images

One of the weak points of most of denoising algoritms (deep learning based ones) is the training data. Due to no or very limited amount of groundtruth data available, these algorithms are often evaluated using synthetic noise models such as Additive Zero-Mean Gaussian noise. The downside of this approach is that these simple model do not represent noise present in natural imagery. For evaluation of denoising algorithms’ performance in poor light conditions, we need either representative models or real noisy images paired with those we can consider as groundtruth. BVI-LOWLIGHT-IMAGES is a dataset of images captured in lowlight condtions. The dataset can to be used as a benchmark in image denoising, image quality assesment.