… dehazing model on synthetic hazy images, which are less able to generalize well to real hazy
images … , which consists of an image translation module and two image dehazing modules. …

… image dehazing utilizes the physical model of hazy image formation in which estimation of
depth or transmission is an important parameter to obtain a haze-free image. … image dehazing …

… image dehazing requires not only that the network encodes highly expressive features but
also that these features are easily recovered to image … image edge regions in image dehazing…

… However, there are missing connection between the features from the downsampling layers
and upsampling layers in our image dehazing network, which causes shallow features (eg. …

… visible object in the image with almost no noise. This paper presents a brief deliberation of
various image dehazing methods that are commonly used. Image dehazing can be used in …

… He divided dehazing algorithms into seven categories, ie, depth estimation, wavelet, … RS
image dehazing algorithms into three categories. The first one is based on image enhancement, …

… of dehazing models trained on synthetic hazy-clean image … Most of them simply formulate
dehazing and rehazing cycles, … -augmented image dehazing framework, termed D4 (Dehazing …

… In this paper, we propose a powerful image dehazing method to recover haze-free images
directly. Specifically, the Separable Hybrid Attention is designed to better perceive the haze …

… Dual-Guidance Network (FSDGN) for single-image dehazing. From a new perspective,
we address image dehazing by jointly exploring the information in the frequency and spatial …

… , which can process 4K (3840 × 2160) resolution images at 125 fps. • We deploy edge-… 4K
image dataset for image dehazing. Experimental results on synthetic and real-world images …