Results 41 to 50 of about 11,754,470 (203)
Image Dehazing Based on Improved Color Channel Transfer and Multiexposure Fusion
Advances in Multimedia, 2023 Image dehazing is one of the problems that need to be solved urgently in the field of computer vision. In recent years, more and more algorithms have been applied to image dehazing and achieved good results.
Shaojin Ma +7 more
doaj +1 more source
AED-Net: A Single Image Dehazing
IEEE Access, 2022 In the past decade, significant research effort has been directed toward developing single-image dehazing algorithms. Despite this effort, dehazing continues to present a challenge, particularly in complex real-world cases.
Sargis A. Hovhannisyan +3 more
doaj +1 more source
On the Duality Between Retinex and Image Dehazing [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 Image dehazing deals with the removal of undesired loss of visibility in outdoor images due to the presence of fog. Retinex is a color vision model mimicking the ability of the Human Visual System to robustly discount varying illuminations when observing a scene under different spectral lighting conditions.
Adrian Galdran +4 more
openaire +5 more sources
Image Dehazing in Disproportionate Haze Distributions [PDF]
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 robustness of these systems.
Shih-Chia Huang +7 more
openaire +2 more sources
Single image dehazing using deep neural networks [PDF]
, 2019 The rapid growth in computer vision applications that are affected by environmental conditions challenge the limitations of existing techniques. This is driving the development of new deep learning based vision techniques that are robust to environmental
Rahmani, Hossein +2 more
core +4 more sources
Image dehazing based on double branch convolution and detail enhancement
Xibei Gongye Daxue XuebaoBecause of detail loss, color distortion and contrast reduction in the image dehazing process in a haze condition, we proposed the image dehazing network based on double branch convolution and detail enhancement, which consists of image dehazing module ...
ZHAI Fengwen, ZHU Yutong, JIN Jing
doaj +1 more source
Image dehazing technique based on polarimetric spectral analysis
, 2016 Image took under hazy weather suffers from poor contrast and resolution, the haze particles will attenuate the light reflected by the targets and add unwanted scattering light.
Xia, Pu, Liu, Xuebin
core +1 more source
NEAR-INFRARED GUIDED COLOR IMAGE DEHAZING [PDF]
, 2013 Near-infrared (NIR) light has stronger penetration capability than visible light due to its long wavelength, thus being less scattered by particles in the air.
Xiaopeng Zhang +9 more
core +3 more sources
Enhance Low Visibility Image Using Haze-Removal Framework
IEEE Access, 2023 We proposed a novel image enhancement framework to raise the visibility of the image’s content. Our primary concern is eliminating haze-like effects and simultaneously increasing images’ brightness.
Ping Juei Liu
doaj +1 more source
Semantic Single-Image Dehazing
CoRR, 2018 Single-image haze-removal is challenging due to limited information contained in one single image. Previous solutions largely rely on handcrafted priors to compensate for this deficiency. Recent convolutional neural network (CNN) models have been used to learn haze-related priors but they ultimately work as advanced image filters.
Ziang Cheng +3 more
openaire +2 more sources