Results 51 to 60 of about 3,318 (186)
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
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A Framework for Objective Evaluation of Single Image De-Hazing Techniques
IEEE Access, 2021 Real-world environment, where images are acquired with digital camera, may be subject to sever climatic conditions such as haze that may drastically reduce the quality performance of sophisticated computer vision algorithms used for various tasks, e.g ...
Alessandro Artusi +1 more
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A Variational Framework for Single Image Dehazing [PDF]
, 2015 Images captured under adverse weather conditions, such as haze or fog, typically exhibit low contrast and faded colors, which may severely limit the visibility within the scene. Unveiling the image struc- ture under the haze layer and recovering vivid colors out of a single image remains a challenging task, since the degradation is depth-dependent and ...
Adrian Galdran +3 more
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Towards Domain Invariant Single Image Dehazing
Proceedings of the AAAI Conference on Artificial Intelligence, 2021 Presence of haze in images obscures underlying information, which is undesirable in applications requiring accurate environment information. To recover such an image, a dehazing algorithm should localize and recover affected regions while ensuring consistency between recovered and its neighboring regions.
Shyam, Pranjay +2 more
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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 +6 more
wiley +1 more source
Haze-Aware Attention Network for Single-Image Dehazing
Applied SciencesSingle-image dehazing is a pivotal challenge in computer vision that seeks to remove haze from images and restore clean background details. Recognizing the limitations of traditional physical model-based methods and the inefficiencies of current ...
Lihan Tong +4 more
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Single Image Dehazing Algorithm Based on Multi-scale Image Fusion [PDF]
Jisuanji gongcheng, 2016 To effectively improve the quality of the degraded image in foggy days,this paper proposes a dehazing algorithm for single image based on multi-scale image fusion.After the image is converted to gradient domain,each scale value is calculated by means of ...
PAN Lei,ZHENG Yijun
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IET Image Processing, Volume 20, Issue 1, January/December 2026.This paper proposes a novel image enhancement method, WCTE, which integrates Haar wavelet transform and adaptive CLAHE to improve the visibility of low‐contrast tablet images. Combined with the YOLOv11 model, this approach significantly boosts defect detection accuracy, especially for half‐grain and paste tabtal.
Zimei Tu +3 more
wiley +1 more source
Progressive Knowledge Distillation for Edge‐Deployable Solder Joint Segmentation
IET Image Processing, Volume 20, Issue 1, January/December 2026.Solder‐Yolo is a lightweight deep learning model based on YOLOv8‐seg, designed for high‐precision solder joint inspection in FPC ribbon cables. It incorporates model pruning, knowledge distillation and a hierarchical context attention module to achieve 96.7% precision and 91.3% mAP while maintaining high inference speed.
Kunhong Li +4 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
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