Results 101 to 110 of about 3,779 (211)

SAD-Net: a full spectral self-attention detail enhancement network for single image dehazing

Scientific Reports
Single-image dehazing technology plays a significant role in video surveillance and intelligent transportation. However, existing dehazing methods using vanilla convolution only extract features in the temporal domain and lack the ability to capture ...
Qingjun Niu, Kun Wu, Jialu Zhang, Zhenqi Han, Lizhuang Liu   +4 more
doaj   +1 more source

Density-Guided and Frequency Modulation Dehazing Network for Remote Sensing Images

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Remote sensing image (RSI) dehazing methods have gained significant attention for their ability to restore clear images, which are crucial for applications such as mineral exploration and flood range forecasting.
Haijun Liu, Jiachen Huang, Jing Nie, Jin Xie, Lihui Chen, Xichuan Zhou   +5 more
doaj   +1 more source

A Physics-Guided Dehazing Method Based on Polarization Imaging

Photonics
Haze conditions degrade image quality via atmospheric scattering and absorption, posing challenges for optical imaging applications. In recent years, deep learning has emerged as an effective method for dehazing images. However, data-driven deep learning
Manjun Yan, Qiuju Wu, Long Ma
doaj   +1 more source

End-to-End United Video Dehazing and Detection

, 2018
The recent development of CNN-based image dehazing has revealed the effectiveness of end-to-end modeling. However, extending the idea to end-to-end video dehazing has not been explored yet.
Li, Boyi, Xu, Jizheng, Peng, Xiulian, Wang, Zhangyang, Feng, Dan, Dan Feng, Xiulian Peng, Jizheng Xu, Zhangyang Wang, Boyi Li   +9 more
core   +1 more source

DehazeMamba: large multi-modal model guided single image dehazing via mamba

Visual Intelligence
Deep neural networks have achieved significant success in image dehazing. However, existing backbones face an irreconcilable trade-off between the global receptive field and computational efficiency, hindering further applications.
Ruikun Zhang, Zhiyuan Yang, Liyuan Pan
doaj   +1 more source

Dehazing with STRESS

, 2015
There exist today plenty of algorithms and many papers about dehazing or defogging, that is enhancing images taken in hazy or foggy conditions. To our knowledge none of them has got a signifcant result for dense and non-dense haze image at the same time.
openaire   +1 more source

HazeCLIP: Towards Language Guided Real-World Image Dehazing [PDF]

Existing methods have achieved remarkable performance in image dehazing, particularly on synthetic datasets. However, they often struggle with real-world hazy images due to domain shift, limiting their practical applicability.
Li, Chunyi, Min, Xiongkuo, Zhang, Zicheng, Li, Wenhao, Liu, Xiaohong, Wang, Ruiyi, Zhai, Guangtao   +6 more
core   +1 more source

DEMANet: A dehazing enhanced multi-branch attention network for remote sensing images. [PDF]

PLoS One
Liu P, Liu S, He P, Wang G.
europepmc   +1 more source

Multi-scale attentional feature fusion-based traffic sign detection using image dehazing process of SPP-CAE and improved optimization of YOLOv9 model. [PDF]

Front Artif Intell
V T, Cm V.
europepmc   +1 more source

Self-Supervised Decoupled Polarization Image Dehazing with an Angle-of-Polarization Frequency-Domain Prior. [PDF]

J Imaging
Cui L, Zong Y, Kong F, Li J.
europepmc   +1 more source