We propose a weighted variational model to estimate both the reflectance and the
illumination from an observed image. We show that, though it is widely adopted for ease of …

Retinex theory is developed mainly to decompose an image into the illumination and
reflectance components by analyzing local image derivatives. In this theory, larger …

In this paper, we propose a novel Retinex-based fractional-order variational model for
severely low-light images. The proposed method is more flexible in controlling the …

Image captured underwater often suffers from low contrast, color distortion and noise
problems, which is caused by absorbing and scattering before the light reaches the camera …

Enhancing low-light image visibility is a critical task in computer vision since it helps to
improve input for high-level algorithms. High-quality images typically have clear structural …

To solve the problem of simultaneously estimating the illumination and reflectance (IR) from
a single image based on the Retinex theory, an effective way is utilizing a Maximum-a …

Images captured under low-light conditions are characterized by problems, including low
brightness, low contrast, and color distortion. Low-light image enhancement, aims to …

The Retinex model is one of the most representative and effective methods for low-light
image enhancement. However, the Retinex model does not explicitly tackle the noise …

This paper proposes a variational model with barriers for Retinex, borrowing the ideas of
barrier methods. We first present an energy functional and then deduce a new energy …

Retinex theory is developed mainly to decompose an image into the product of illumination
and reflectance based on local derivatives, in which smaller derivatives are given to the …