Low-light images are not conducive to human observation and computer vision algorithms
due to their low visibility. To solve this problem, many image enhancement techniques have …

Low-light image enhancement based on deep convolutional neural networks (CNNs) has
revealed prominent performance in recent years. However, it is still a challenging task since …

Low-light image enhancement algorithms can improve the visual quality of low-light images
and support the extraction of valuable information for some computer vision techniques …

Image enhancement is a fundamental low-level task of significant importance that can
directly affect high-level image processing tasks. Although various methods have been …

The rising demand for high quality display has ensued active research in high dynamic
range (HDR) imaging, which has the potential to replace the standard dynamic range …

The visual quality of photographs taken under imperfect lightness conditions can be
degenerated by multiple factors, eg, low lightness, imaging noise, color distortion, and so on …

Although agreement between the annotators who mark feature locations within images has
been studied in the past from a statistical viewpoint, little work has attempted to quantify the …

Low light image enhancement algorithms intent to produce visually pleasant images and
target to extract valuable information for computer vision applications. The task of improving …

Non-uniform illumination images are of limited visibility due to under-exposure, over-
exposure, or a combination of these two factors. Enhancing these images is a very …

Many robotic and machine-vision applications rely on the accurate results of stereo
correspondence algorithms. However, difficult environmental conditions, such as …