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Reliable image dehazing by NeRF
Optics ExpressImage dehazing is a typical low-level visual task. With the continuous improvement of network performance and the introduction of various prior knowledge, the ability of image dehazing is becoming stronger. However, the existing dehazing methods have problems such as the inability to obtain real shooting datasets, unreliable dehazing processes, and the
Zheyan Jin +4 more
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Multiscale implicit frequency selective network for single-image dehazing
ETRI JournalImage dehazing is aimed to reconstruct a clear latent image from a degraded image affected by haze. Although vision transformers have achieved impressive success in various computer vision tasks, the limitations in scale and quality of available datasets
Zhibo Wang, Jia Jia, Jeongik Min
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GUSL-Dehaze: A Green U-Shaped Learning Approach to Image Dehazing
2025 IEEE 8th International Conference on Multimedia Information Processing and Retrieval (MIPR)Image dehazing is a restoration task that aims to recover a clear image from a single hazy input. Traditional approaches rely on statistical priors and the physics-based atmospheric scattering model to reconstruct the haze-free image. While recent state-of-the-art methods are predominantly based on deep learning architectures, these models often ...
Movaheddrad, Mahtab +2 more
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DehazeMamba: large multi-modal model guided single image dehazing via mamba
Visual IntelligenceDeep 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
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Density-Guided and Frequency Modulation Dehazing Network for Remote Sensing Images
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingRemote 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 +5 more
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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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Pixel-Dehaze: Deciphering Dehazing Through Regression-Based Depth and Scattering Estimation
Big Data and Cognitive ComputingHaze significantly reduces visibility in critical applications such as autonomous driving, surveillance, and firefighting, making its removal essential for safety and reliability. Motivated by the limited robustness of the existing methods under non-uniform haze conditions, this study introduces a novel regression-based dehazing model that ...
Vaibhav Baldeva +5 more
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, 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.
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Dehaze-attention: enhancing image dehazing with a multi-scale, attention-based deep learning framework. [PDF]
Sci RepHuang H, Ho GTS, Geda MW, Li M, Tang YM.
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From Controlled Scenarios to the Real World: Cross-Domain Degradation Pattern Matching for All-in-One Image Restoration. [PDF]
Research (Wash D C)Fan J +7 more
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