This paper reviews the NTIRE 2020 Challenge on NonHomogeneous Dehazing of images
(restoration of rich details in hazy image). We focus on the proposed solutions and their …

Low-light image enhancement is a notoriously challenging problem. Enhancement of low-
light images is intended to increase contrast, adjust the tone, suppress noise, and produce …

This paper presents an optimization-based low-light image enhancement method using
spatially adaptive l 2-norm based Retinex model. The proposed method adaptively enforces …

While the retinex theory aimed at explaining human color perception, its derivations have
led to efficient algorithms enhancing local image contrast, thus permitting among other …

Image captured under poor-illumination conditions often display attributes of having poor
contrasts, low brightness, a narrow gray range, colour distortions and considerable …

In this paper, we present a three-stage method for the estimation of the color of the illuminant
in RAW images. The first stage uses a convolutional neural network that has been specially …

Image dehazing deals with the removal of undesired loss of visibility in outdoor images due
to the presence of fog. Retinex is a color vision model mimicking the ability of the Human …

In 1964, Edwin H. Land formulated the Retinex theory, the first attempt to simulate and
explain how the human visual system perceives color. His theory and an extension, the …

Starting from the revolutionary Retinex by Land and McCann, several further perceptually
inspired color correction models have been developed with different aims, eg reproduction …

We present an interpretation of Land's Retinex theory that we show to be consistent with the
original formulation. The proposed model relies on the computation of the expectation value …