Nighttime Image Dehazing by Render. [PDF]
J Imaging, 2023 Nighttime image dehazing presents unique challenges due to the unevenly distributed haze caused by the color change of artificial light sources. This results in multiple interferences, including atmospheric light, glow, and direct light, which make the complex scattering haze interference difficult to accurately distinguish and remove.
Jin Z, Feng H, Xu Z, Chen Y.
europepmc +6 more sources
Benchmarking Single-Image Dehazing and Beyond [PDF]
IEEE Transactions on Image Processing, 2019 IEEE Transactions on Image Processing(TIP 2019)
Wenqi Ren +2 more
exaly +5 more sources
Multi-Scale Attention Feature Enhancement Network for Single Image Dehazing [PDF]
Sensors, 2023 Aiming to solve the problem of color distortion and loss of detail information in most dehazing algorithms, an end-to-end image dehazing network based on multi-scale feature enhancement is proposed.
Weida Dong +4 more
doaj +2 more sources
Image dehazing algorithm based on deep transfer learning and local mean adaptation [PDF]
Scientific ReportsIn recent years, haze has significantly hindered the quality and efficiency of daily tasks, reducing the visual perception range. Various approaches have emerged to address image dehazing, including image enhancement, restoration, and deep learning-based
Dongyang Shi, Sheng Huang
doaj +2 more sources
MLCANet: Multi-Level Composite Attention-Guided Network for Non-Homogeneous Image Dehazing in Adverse Weather Conditions [PDF]
SensorsImage dehazing is a challenging ill-posed problem in low-level computer vision tasks, requiring the restoration of high-quality, haze-free images from complex and foggy conditions.
Yongsheng Qiu
doaj +2 more sources
Hazediff: A training-free diffusion-based image dehazing method with pixel-level feature injection. [PDF]
PLoS ONEIn the current environmental context, significant emissions generated by industrial and transportation activities, coupled with an unreasonable energy structure, have resulted in recurrent haze phenomena.
Xiaoxia Lin +8 more
doaj +2 more sources
Adaptive haze pixel intensity perception transformer structure for image dehazing networks [PDF]
Scientific ReportsIn the realm of deep learning-based networks for dehazing using paired clean-hazy image datasets to address complex real-world haze scenarios in daytime environments and cross-dataset challenges remains a significant concern due to algorithmic ...
Jing Wu +3 more
doaj +2 more sources
Atmospheric Light Estimation Using Polarization Degree Gradient for Image Dehazing [PDF]
SensorsA number of image dehazing techniques depend on the estimation of atmospheric light intensity. The majority of dehazing algorithms do not incorporate a physical model to estimate atmospheric light, leading to reduced accuracy and significantly impacting ...
Shuai Liu +5 more
doaj +2 more sources
Contrastive Multiscale Transformer for Image Dehazing. [PDF]
Sensors (Basel)Images obtained in an unfavorable environment may be affected by haze or fog, leading to fuzzy image details, low contrast, and loss of important information. Recently, significant progress has been achieved in the realm of image dehazing, largely due to the adoption of deep learning techniques.
Chen J, Zhao G.
europepmc +4 more sources
AgriGAN: unpaired image dehazing via a cycle-consistent generative adversarial network for the agricultural plant phenotype [PDF]
Scientific ReportsArtificially extracted agricultural phenotype information exhibits high subjectivity and low accuracy, while the utilization of image extraction information is susceptible to interference from haze.
Jin-Ting Ding +3 more
doaj +2 more sources