Results 51 to 60 of about 16,734,778 (159)

PFONet: A Progressive Feedback Optimization Network for Lightweight Single Image Dehazing

, 2023
Image dehazing is an effective means to enhance the quality of images captured in foggy or hazy weather conditions. However, existing image dehazing methods are either ineffective in dealing with complex haze scenes, or incurring too much computation. To
Xiang, Wei, Ren, Wenqi, Li, Shuoshi, Zhou, Yuan   +3 more
core   +1 more source

Image Haze Removal Based on Superpixels and Markov Random Field

IEEE Access, 2020
Image haze removal is critical for autonomous driving. However, it is a challenging task for the existing image dehazing algorithms to eliminate the block effect completely and handle objects similar to light (such as snowy objects and white buildings ...
Yibo Tan, Guoyu Wang
doaj   +1 more source

Deformable Attention Multiscale Feature Fusion Network‐Dehaze: An Adaptive Image Dehazing Method Based on Deformable Attention Multiscale Fusion Network

Advanced Intelligent Systems, Volume 8, Issue 5, May 2026.
This paper presents the deformable attention multiscale feature fusion network‐dehaze adaptive image dehazing network, which integrates three core modules (revised residual shrinkage unit, multiscale attention, cross‐scale feature fusion). It incorporates deformable convolution and multiscale attention mechanisms to address the detail loss issue of ...
Ruipeng Wang, Yajun Chen, Hao Liu, Mingrui Li, Zhiqi Li   +4 more
wiley   +1 more source

Sea Ice Floe Segmentation in Close‐Range Optical Imagery Using Active Contour and Foundation Models

Earth and Space Science, Volume 13, Issue 2, February 2026.
Abstract The size of sea ice floes in the marginal ice zone (MIZ) is a key factor influencing ice coverage, albedo, wave propagation, and ocean–atmosphere energy exchanges. Floe size can be observed by processing visual‐range imagery from ships, aircraft, or satellites.
Giulio Passerotti, Alberto Alberello, Marcello Vichi, Luke G. Bennetts, James Bailey, Alessandro Toffoli   +5 more
wiley   +1 more source

Spatial-frequency complementary fusion network for dehazing with multi-scale and attention modules

Scientific Reports
Single image dehazing is a challenging ill-posed problem. It aims to estimate the latent haze-free image from the observed hazy image. In recent years, learning-based methods have demonstrated their superiority in single image dehazing.
Chenguang Yan, Gang Liu
doaj   +1 more source

Perceptual evaluation of single image dehazing algorithms

, 2015
Images captured in outdoor scenes often suffer from poor visibility and color shift due to the presence of haze. Although many algo-rithms have been proposed to remove the haze, not much effort has been made on quality assessment of dehazed images.
Zhou Wang, Wentao Liu, Kede Ma
core   +1 more source

High-Resolution Representations Network for Single Image Dehazing

Sensors, 2022
Deep learning-based image dehazing methods have made great progress, but there are still many problems such as inaccurate model parameter estimation and preserving spatial information in the U-Net-based architecture. To address these problems, we propose
Wensheng Han, Hong Zhu, Chenghui Qi, Jingsi Li, Dengyin Zhang   +4 more
doaj   +1 more source

Artificial Compound Eye for Clear Vision in Harsh Environment

Advanced Functional Materials, Volume 36, Issue 4, 12 January 2026.
Artificial compound eye (CE) with exceptional imaging and motion tracking capturing the movement of a spider and swinging thread with a wide field of view. Surface modifications ensure clear vision of alphabetic letters in rain and fog. Images captured in fog with CE remains visible 3 times longer than simple eyes (SE).
Kehinde Kassim, Qiuyun Lu, Hao Xuan, Nobuo Maeda, Xingyu Li, Ben Bin Xu, Xuehua Zhang   +6 more
wiley   +1 more source

Single Image Dehazing Using Sparse Contextual Representation

Atmosphere, 2021
In this paper, we propose a novel method to remove haze from a single hazy input image based on the sparse representation. In our method, the sparse representation is proposed to be used as a contextual regularization tool, which can reduce the block ...
Jing Qin, Liang Chen, Jian Xu, Wenqi Ren
doaj   +1 more source

Progressive residual learning for single image dehazing

CoRR, 2021
The recent physical model-free dehazing methods have achieved state-of-the-art performances. However, without the guidance of physical models, the performances degrade rapidly when applied to real scenarios due to the unavailable or insufficient data problems.
Yudong Liang, Bin Wang 0071, Jiaying Liu 0001, Deyu Li, Yuhua Qian, Wenqi Ren   +5 more
openaire   +3 more sources