Haziness Degree Evaluator: A Knowledge-Driven Approach for Haze Density Estimation [PDF]
Sensors, 2021 Haze is a term that is widely used in image processing to refer to natural and human-activity-emitted aerosols. It causes light scattering and absorption, which reduce the visibility of captured images. This reduction hinders the proper operation of many
Dat Ngo, Gi-Dong Lee, Bongsoon Kang
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DCAF-Net: Density-Conditioned Attention Fusion Network for Single-Image Dehazing [PDF]
SensorsSingle-image dehazing aims to recover clear scenes from degraded images affected by atmospheric scattering, serving as a critical preprocessing technique for improving the imaging quality of visual sensors.
Nianfeng Li +5 more
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AMSA-Net: attention-based multi-scale feature aggregation network for single image dehazing [PDF]
Frontiers in NeuroroboticsProblemDeep learning technology promotes the development of single-image dehazing. However, many existing methods fail to fully consider the haze density and its spatial distribution, which limits the improvement of dehazing performance.Proposed ...
Shanqin Wang +3 more
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Autonomous Single-Image Dehazing: Enhancing Local Texture with Haze Density-Aware Image Blending
Remote SensingSingle-image dehazing is an ill-posed problem that has attracted a myriad of research efforts. However, virtually all methods proposed thus far assume that input images are already affected by haze. Little effort has been spent on autonomous single-image
Siyeon Han +3 more
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HDSA-Net: Haze Density and Semantic Awareness Network for Hyperspectral Image Dehazing
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingHyperspectral image (HSI) dehazing is a challenging task due to the complex imaging conditions. Existing deep learning-based dehazing methods neither fully consider the physical characteristics of HSIs, nor take advantage of high-level semantic ...
Qianru Liu +5 more
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A SINGLE IMAGE DEHAZING DATASET WITH LOW-LIGHT REAL-WORLD INDOOR IMAGES, DEPTH MAPS AND INFRARED IMAGES [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2023 Benchmarking of haze removal methods and training related models requires appropriate datasets. The most objective metrics of assessment quality of dehazing are shown by reference metrics – i.e. those in which the reconstructed image is compared with the
A. Filin, A. Kopylov, I. Gracheva
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Automating a Dehazing System by Self-Calibrating on Haze Conditions
Sensors, 2021 Existing image dehazing algorithms typically rely on a two-stage procedure. The medium transmittance and lightness are estimated in the first stage, and the scene radiance is recovered in the second by applying the simplified Koschmieder model.
Dat Ngo +3 more
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Equivalent analysis of contaminations under simulated fog-haze and natural fog-haze
电力工程技术, 2022 The uncertainty of haze weather makes it difficult to carry out research on its impact on power equipment. However,whether the research under simulated haze environment is equivalent to that under actual haze weather is related to the guiding value of ...
WANG Jianhui +5 more
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Image Dehazing in Disproportionate Haze Distributions
IEEE Access, 2021 Haze removal techniques employed to increase the visibility level of an image play an important role in many vision-based systems. Several traditional dark channel prior-based methods have been proposed to remove haze formation and thereby enhance the ...
Shih-Chia Huang +7 more
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A new end-to-end image dehazing algorithm based on residual attention mechanism
Xibei Gongye Daxue Xuebao, 2021 Traditional image dehazing algorithms based on prior knowledge and deep learning rely on the atmospheric scattering model and are easy to cause color distortion and incomplete dehazing.
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