Low-light image enhancement is generally regarded as a challenging task in image
processing, especially for the images captured at nighttime or images taken in low-light …

In computer vision, low-light image enhancement has always been a challenging task
caused by more lower signal to noise ratio. Some methods have been proposed to enhance …

Low-light image enhancement (LLIE) aims at improving the perception or interpretability of
an image captured in an environment with poor illumination. Recent advances in this area …

Due to the low visibility of the low-light image, it is not conducive to human observation and
computer vision algorithm. Inspired by the human vision system (HVS), we propose a simple …

Recent years, researches in low-light image enhancement has done quite a lot and shown
great success in real life application. In this paper, a modified U-Net-based method is …

This study introduces a low-light image enhancement method using a hybrid deep-learning
network and mixed-norm loss functions, in which the network consists of a decomposition …

Because of the low-light shooting environment, the camera sensor will loss huge details and
fuzzy edge. A deep low-light residual convolutional network (LRCNN) is proposed in this …

Images taken under low light or dim backlight conditions usually have insufficient brightness,
low contrast, and poor visual quality of the image, which leads to increased difficulty in …

Low-light image enhancement is one of the most challenging tasks in computer vision, and it
is actively researched and used to solve various problems. Most of the time, image …

In this paper, we propose a CNN based method to perform low-light image enhancement.
We design a special module to utilize multiscale feature maps, which can avoid gradient …