Remote sensing images (RSIs) captured in haze weather will suffer from serious quality degradation with color distortion and contrast reduction, which creates numerous challenges for the utilization of RSIs. To address these issues, this paper proposes a novel removal algorithm, named HALP, visible RSIs based on heterogeneous atmospheric light prior side window filter. HALP is comprised two key...

Haze-level discriminators are highly desirable for autonomous vehicles to handle segmentation tasks successfully in hazy and foggy outdoor environments. Neural networks trained detect clear images show more false positives unrecognize the pixel patterns class categories when they encounter images. Here, we propose a novel dehazing scheme called Adaptive Dehazing (AD) which can separate unaccept...

The presence of haze significantly degrades the quality remote sensing images, resulting in issues such as color distortion, reduced contrast, loss texture, and blurred image edges, which can ultimately lead to failure application systems. In this paper, we propose a superpixel-based visible dehazing algorithm, namely SRD. To begin, images are divided into content-aware patches using superpixel...