Results 91 to 100 of about 16,734,778 (159)

Depth-Guided Bilateral Grid Feature Fusion Network for Dehazing

Sensors
In adverse foggy weather conditions, images captured are adversely affected by natural environmental factors, resulting in reduced image contrast and diminished visibility.
Xinyu Li, Zhi Qiao, Gang Wan, Sisi Zhu, Zhongxin Zhao, Xinnan Fan, Pengfei Shi, Jin Wan   +7 more
doaj   +1 more source

Initial Results in Underwater Single Image Dehazing [PDF]

, 2010
As light is transmitted from subject to observer it is absorbed and scattered by the medium it passes through. In mediums with large suspended particles, such as fog or turbid water, the effect of scattering can drastically decrease the quality of images.
Carlevaris-Bianco, Nicholas, R M Eustice, Mohan, Anush, Eustice, Ryan M., A Mohan, N Carlevaris-Bianco   +5 more
core   +1 more source

Improved single image dehazing using guided filter

, 2011
Single image dehazing is challenging because it is massively ill-posed. Haze removal based on dark channel prior is effective, but refining the transmission map with closed-form matting is computationally expensive.
Au, Oscar C., Guo, Zheng, Pang, Jiahao
core  

Interaction-Guided Two-Branch Image Dehazing Network

Image dehazing aims to restore clean images from hazy ones. Convolutional Neural Networks (CNNs) and Transformers have demonstrated exceptional performance in local and global feature extraction, respectively, and currently represent the two mainstream ...
Li, Xiaosong, Tan, Tianshu, Liu, Huichun
core   +2 more sources

Robust regularization for single image dehazing

Journal of King Saud University - Computer and Information Sciences, 2022
Usman Ali 0006, Ikhyun Lee, Muhammad Tariq Mahmood   +2 more
openaire   +1 more source

Single Image Dehazing Based on Generic Regularity

CoRR, 2018
Submitted to ...
Kushal Borkar, Snehasis Mukherjee
openaire   +3 more sources

Single image dehazing based on contrast enhancement

, 2011
A simple and adaptive single image dehazing algorithm is proposed in this work. Based on the observation that a hazy image has low contrast in general, we attempt to restore the original image by enhancing the contrast.
Jin-Hwan Kim, Sim, Jae-Young, Kim, Jin-Hwan, Jae-Young Sim, Kim, Chang-Su, Chang-Su Kim   +5 more
core   +1 more source

Feature attention gated context aggregation network for single image dehazing and its application on unmanned aerial vehicle images

IET Cyber-Physical Systems
Single‐image dehazing is a highly challenging ill‐posed task in the field of computer vision. To address this, a new image dehazing model with feature attention, named feature attention gated context aggregation network (FAGCA‐Net), is proposed to tackle
Yongquan Wu, Xuan Zhao, Xinsheng Zhang, Tao Long, Ping Luo   +4 more
doaj   +1 more source

A bi‐stream transformer for single‐image dehazing

ETRI Journal
Abstract Deep‐learning methods, such as encoder–decoder networks, have achieved impressive results in image dehazing. However, these methods often rely only on synthesized data for training that limits their generalizability to hazy, real‐world images.
Mingrui Wang, Jinqiang Yan, Chaoying Wan, Guowei Yang, Teng Yu   +4 more
openaire   +2 more sources

Joint dual-teacher distillation and unsupervised fusion for unpaired real-world image dehazing

Complex & Intelligent Systems
Existing learning-based dehazing algorithms struggle to deal with real world hazy images for lack of paired clean data. Moreover, most dehazing methods require significant computation and memory.
Yingxu Qiao, Xiyan Zhan, Fen Luo, Zhanqiang Huo   +3 more
doaj   +1 more source