Results 51 to 60 of about 3,779 (211)

Single image dehazing based on hazy features extraction and enhancement network

Journal of Measurement Science and Instrumentation, 2023
Convolutional neural network is developing rapidly in image processing. Most image dehazing algorithms only focus on dehazing but neglect the overall quality of dehazing image, which leads to problems such as loss of information blurred texture, etc.
ZHANG Jinlong, YANG Yan
doaj  

Large‐scale characterization of horizontal forest structure from remote sensing optical images

Remote Sensing in Ecology and Conservation, Volume 12, Issue 4, Page 611-628, August 2026.
Sub‐meter resolution remote sensing data and tree crown segmentation techniques hold promise in offering detailed information that can support the characterization of forest structure from a horizontal perspective, offering new insights in the tree crown structure at scale.
Xin Xu, Martin Brandt, Xiaowei Tong, Maurice Mugabowindekwe, Yuemin Yue, Sizhuo Li, Qiue Xu, Siyu Liu, Florian Reiner, Kelin Wang, Zhengchao Chen, Yongqing Bai, Rasmus Fensholt   +12 more
wiley   +1 more source

Advances in Single-Image Dehazing via Unsupervised Learning [PDF]

Jisuanji kexue yu tansuo
Image dehazing is an important research direction in image restoration for computer vision. Publicly available datasets are mainly dominated by large-scale synthetic hazy image datasets, while real-world hazy image datasets remain relatively limited.
ZHANG Mengmeng, YANG Ying, ZHAO Jia, WANG Huiling
doaj   +1 more source

Task‐Aligned Haze Removal With Semantic‐Aware Fusion and Contrast Self‐Correction

CAAI Transactions on Intelligence Technology, Volume 11, Issue 4, Page 978-993, August 2026.
ABSTRACT Adverse haze conditions introduce complex degradations that obscure scene details and distort structural cues critical for object detection, posing persistent challenges for vision‐based sensing systems. Although existing haze removal methods have achieved notable improvements in visual clarity, their optimisation objectives are often ...
Jinbin Wang, Aiping Yang, Guosong Jiang, Wenlong Yu, Dongwei Ren, Qinghua Hu   +5 more
wiley   +1 more source

Progressive Colour Equalisation and Detail Refinement for Underwater Image Enhancement

CAAI Transactions on Intelligence Technology, Volume 11, Issue 3, Page 709-725, June 2026.
ABSTRACT Underwater image enhancement remains a critical challenge in computational vision due to complex distortions caused by wavelength‐dependent light absorption and scattering. This paper introduces CEDFNet, a novel two‐stage framework that leverages advanced computational intelligence techniques for robust and high‐fidelity underwater image ...
Songbai Liu, Jiacheng Huang
wiley   +1 more source

Image and video dehazing by regularized optimization

, 2017
Images and videos captured in hazy weather often yield low contrast and offer limited visibility due to the presence of haze in the atmosphere. Dr Jiaxi studied the image and video dehazing problem.
Jiaxi He (3115425)
core   +1 more source

A Nighttime and Daytime Single-Image Dehazing Method

, 2022
In this study, the requirements for image dehazing methods have been put forward, such as a wider range of scenarios in which the methods can be used, faster processing speeds and higher image quality.
Yin Xiang, Yunqing Tang, Guangfeng Chen
core   +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

DeepVideoDehazeNet: A Comprehensive Deep Learning Approach for Video Dehazing Using Diverse Datasets [PDF]

International Journal of Mathematical, Engineering and Management Sciences
Video dehazing is a technique commonly used to enhance the quality of videos that appear hazy or degraded due to factors like air scattering and light absorption.
Sandeep Vishwakarma, Anuradha Pillai, Deepika Punj   +2 more
doaj   +1 more source

Polarimetric dehazing method for visibility improvement based on visible and infrared image fusion

, 2016
Polarimetric dehazing methods have proven effective in enhancing the quality of chromatic hazy images. Considering that the infrared radiance has a better capacity for traveling through the haze, in this paper we propose a polarimetric dehazing method ...
Zhang, Wenfei, Ren, Liyong, Ren, Liyong (renliy@opt.ac.cn), Liang, Jian, Ju, Haijuan, Qu, Enshi   +5 more
core   +1 more source