Remote sensing images are widely used in object detection and tracking, military security,
and other computer vision tasks. However, remote sensing images are often degraded by …

Multispectral remote sensing (RS) images are often contaminated by the haze that degrades
the quality of RS data and reduces the accuracy of interpretation and classification …

The natural and artificial dispersal of climatic particles transforms images obtained in open-
air conditions. Due to visibility diminishing aerosols, unfavorable climate situations such as …

Fog in hyperspectral images severely limits the visibility of imaging scene and reduces the
image contrast, which has a negative effect on the following image interpretation. Defogging …

Haze removal is a pre-processing step that operates on at-sensor radiance data prior to the
physically based image correction step to enhance hazy imagery visually. Most current haze …

Nonuniform haze on remote sensing images degrades image quality and hinders many high-
level tasks. In this paper, we propose a Nonuniformly Dehaze Network towards nonuniform …

Haze contamination is a very common issue in remote sensing images, which inevitably
limits data usability and further applications. Several methods have been developed for …

Abstract Information about the earth's surface is difficult to capture in remote sensing images
because bad weather greatly curtails visibility and diminishes visual contrast in the images …

Visible remotely sensed images usually suffer from the haze, which contaminates the
surface radiation and degrades the data quality in both spatial and spectral dimensions. This …

Optical satellite images are often affected by haze atmospheric conditions, which degrades
the quality of remote sensing (RS) data and reduces the accuracy of interpretation and …