Results 11 to 20 of about 1,385 (183)
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
DUNet: a novel dehazing model based on outdoor images [PDF]
Frontiers in Plant ScienceImage dehazing technology is widely utilized in outdoor environments, especially in precision agriculture, where it enhances image quality and monitoring accuracy.
Wei Zhao +10 more
doaj +2 more sources
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
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
Sparse Depth-Guided Image Enhancement Using Incremental GP with Informative Point Selection
Sensors, 2023 We propose an online dehazing method with sparse depth priors using an incremental Gaussian Process (iGP). Conventional approaches focus on achieving single image dehazing by using multiple channels.
Geonmo Yang +3 more
doaj +1 more source
A novel simulation for polarization dehazing
IEEE Signal Processing Letters, 2023 Haze and fog, as severe weather conditions, have absorbing and scattering effects on the optical images, severely affecting image quality. Polarization-based dehazing algorithms can estimate the original radiance distribution of the scene through the polarization of skylight and transmitted light.
Changda Yan +4 more
openaire +2 more sources
Aerial Image Dehazing Using Reinforcement Learning
Remote Sensing, 2022 Aerial observation is usually affected by the Earth’s atmosphere, especially when haze exists. Deep reinforcement learning was used in this study for dehazing.
Jing Yu +3 more
doaj +1 more source
Single Image Dehazing Using End-to-End Deep-Dehaze Network [PDF]
Electronics, 2020 Haze is a natural distortion to the real-life images due to the specific weather conditions. This distortion limits the perceptual fidelity, as well as information integrity, of a given image. Image dehazing for the observed images is a complicated task because of its ill-posed nature.
Masud An-Nur Islam Fahim, Ho Yub Jung
openaire +2 more sources
Survey of Transformer-Based Single Image Dehazing Methods [PDF]
Jisuanji kexue yu tansuoAs a fundamental computer vision task, image dehazing aims to preprocess degraded images by restoring color contrast and texture information to improve visibility and image quality, thereby the clear images can be recovered for subsequent high-level ...
ZHANG Kaili, WANG Anzhi, XIONG Yawei, LIU Yun
doaj +1 more source
Enhanced Variational Image Dehazing [PDF]
SIAM Journal on Imaging Sciences, 2015 Images obtained under adverse weather conditions, such as haze or fog, typically/nexhibit low contrast and faded colors, which may severely limit the visibility within the scene. Unveiling/nthe image structure under the haze layer and recovering vivid colors out of a single image/nremains a challenging task, since the degradation is depth-dependent and
Adrian Galdran +3 more
openaire +2 more sources