Given that a single remote sensing image dehazing is an ill‐posed problem, this is still a
challenging task. In order to improve the visibility of a single hazy remote sensing …

The increasing urbanisation trend over the decades has resulted in the rapid transformation
of land use and land cover (LULC) patterns worldwide. One of the significant consequences …

Outdoor images are often degraded by haze, causing a change of image contrast and color
values. In this paper, we propose a novel variational model for the removal of haze in a …

A novel strategy is proposed to address block artifacts in a conventional dark channel prior
(DCP). The DCP was used to estimate the transmission map based on patch-based …

The integration of multisource remote sensing data and deep learning models offers new
possibilities for accurately mapping high spatial resolution forest height. We found that GEDI …

A fast and shallow convolutional neural network is proposed for hyperspectral image super-
resolution inspired by Spatial-Spectral Reconstruction Network (SSR-NET). The feature …

This article presents a saliency guided remote sensing image dehazing network model. It
consists of the following three blocks: A dense residual based backbone network, a saliency …

In observation of land information using satellite images, clouds are one of the most serious
obstacles due to their opacity property which can block the visibility of ground objects and …

In foggy or hazy conditions, images are degraded due to the scattering and attenuation of
atmospheric particles, reducing the contrast and visibility and changing the color. This …

Haze is one of the major environmental issues that have continuously vexed countries
worldwide, including Malaysia, for the last three decades. Therefore, this study aims to …