Due to the complexity of real environment and potential defects of current simulation
datasets, either prior-based or deep learning-based single image dehazing methods may …

This paper presents a deep multi-model fusion network to attentively integrate multiple
models to separate layers and boost the performance in single-image dehazing. To do so …

This article introduces a novel solution to improve image enhancement in terms of color
appearance. Our approach, called Color Channel Compensation (3C), overcomes artifacts …

Underwater images play an essential role in acquiring and understanding underwater
information. High-quality underwater images can guarantee the reliability of underwater …

On benchmark images, modern dehazing methods are able to achieve very comparable
results whose differences are too subtle for people to qualitatively judge. Thus, it is …

In this work, a novel and ultra-robust single image dehazing method called IDRLP is
proposed. It is observed that when an image is divided into regions, with each region having …

Low-light image enhancement aims to improve the quality of images captured under low-
lightening conditions, which is a fundamental problem in computer vision and multimedia …

Fog removal from an image is an active research topic in computer vision. However, current
literature is weak in the following two areas which in many ways are hindering progress for …

In this paper, we propose a retinex-based decomposition model for a hazy image and a
novel end-to-end image dehazing network. In the model, the illumination of the hazy image …

We introduce an effective fusion-based technique to enhance both day-time and night-time
hazy scenes. When inverting the Koschmieder light transmission model, and by contrast with …