Deep convolutional networks–based super-resolution is a fast-growing field with numerous
practical applications. In this exposition, we extensively compare more than 30 state-of-the …

Underwater video images, as the primary carriers of underwater information, play a vital role
in human exploration and development of the ocean. Due to the optical characteristics of …

Underwater images are subject to intricate and diverse degradation inevitably affecting the
effectiveness of underwater visual tasks. However most approaches primarily operate in the …

Underwater image enhancement has attracted much attention due to the rise of marine
resource development in recent years. Benefit from the powerful representation capabilities …

Due to the wavelength-dependent light absorption and scattering, the raw underwater
images are usually inevitably degraded. Underwater image enhancement (UIE) is of great …

Underwater image enhancement has received much attention in underwater vision
research. However, raw underwater images easily suffer from color distortion …

Underwater image enhancement (UIE) aims to improve the visual quality of raw underwater
images. Current UIE algorithms primarily train a deep neural network (DNN) on synthetic …

Images captured in underwater structural inspection often suffer from issues such as
blurriness, fogging, distortion, and low resolution due to light absorption and scattering by …

Due to the light absorption and scattering, captured underwater images usually contain
severe color distortion and contrast reduction. To address the above problems, we combine …

The powerful representation capacity of deep learning has made it inevitable for the
underwater image enhancement community to employ its potential. The exploration of deep …