Results 31 to 40 of about 5,362 (169)
Nighttime Image Dehazing by Render
Journal of 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.
Zheyan Jin +3 more
openaire +3 more sources
Fast Execution Schemes for Dark-Channel-Prior-Based Outdoor Video Dehazing
IEEE Access, 2018 This paper studies the dark-channel-prior (DCP)-based dehazing from the implementation perspectives. Several schemes are proposed, in order to realize the fast execution of the DCP-based method targeting the outdoor video dehazing.
Yongmin Park, Tae-Hwan Kim
doaj +1 more source
Single Image Dehazing Using Wavelet-Based Haze-Lines and Denoising
IEEE Access, 2021 Haze reduces the contrast of an image and causes the loss in colors, which has a negative effect on the subsequent object detection; therefore, single image dehazing is a challenging visual task.
Wei-Yen Hsu, Yi-Sin Chen
doaj +1 more source
Fast Deep Multi-patch Hierarchical Network for Nonhomogeneous Image Dehazing
, 2020 Recently, CNN based end-to-end deep learning methods achieve superiority in Image Dehazing but they tend to fail drastically in Non-homogeneous dehazing.
Das, Sourya Dipta, Dutta, Saikat
core +1 more source
Image Dehazing Using LiDAR Generated Grayscale Depth Prior
Sensors, 2022 In this paper, the dehazing algorithm is proposed using a one-channel grayscale depth image generated from a LiDAR point cloud 2D projection image. In depth image-based dehazing, the estimation of the scattering coefficient is the most important.
Won Young Chung +2 more
doaj +1 more source
Multi-Scale Attention Feature Enhancement Network for Single Image Dehazing
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 +1 more source
Region Adaptive Single Image Dehazing [PDF]
Entropy, 2021 Image haze removal is essential in preprocessing for computer vision applications because outdoor images taken in adverse weather conditions such as fog or snow have poor visibility. This problem has been extensively studied in the literature, and the most popular technique is dark channel prior (DCP). However, dark channel prior tends to underestimate
openaire +3 more sources
A Bayesian Framework for Single Image Dehazing considering Noise
The Scientific World Journal, 2014 The single image dehazing algorithms in existence can only satisfy the demand for dehazing efficiency, not for denoising. In order to solve the problem, a Bayesian framework for single image dehazing considering noise is proposed.
Dong Nan +4 more
doaj +1 more source
Learning of Image Dehazing Models for Segmentation Tasks
, 2019 To evaluate their performance, existing dehazing approaches generally rely on distance measures between the generated image and its corresponding ground truth.
berman +9 more
core +1 more source
Model Adaptation with Synthetic and Real Data for Semantic Dense Foggy Scene Understanding
, 2018 This work addresses the problem of semantic scene understanding under dense fog. Although considerable progress has been made in semantic scene understanding, it is mainly related to clear-weather scenes.
A Bar Hillel +20 more
core +1 more source