Results 71 to 80 of about 1,385 (183)
Scientific ReportsIn image dehazing, the dehazing performance in bright regions and the model’s robustness to noise are critical evaluation criteria. However, existing dehazing models often suffer from distortions in the bright areas and exhibit weak noise resistance.
Dongyang Shi, Sheng Huang, Wei Zhao
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Enhance Dehazed Images Rapidly Without Losing Restoration Accuracy
IEEE AccessWe proposed a novel image-enhancing framework to ensure consolidated restoration accuracy when remedying the visual quality of dehazed images, such as over-saturation, color deviation, or luminance issues. Conventionally, the dehazing process was usually
Ping-Juei Liu
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SAD-Net: a full spectral self-attention detail enhancement network for single image dehazing
Scientific ReportsSingle-image dehazing technology plays a significant role in video surveillance and intelligent transportation. However, existing dehazing methods using vanilla convolution only extract features in the temporal domain and lack the ability to capture ...
Qingjun Niu +4 more
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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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A Physics-Guided Dehazing Method Based on Polarization Imaging
PhotonicsHaze conditions degrade image quality via atmospheric scattering and absorption, posing challenges for optical imaging applications. In recent years, deep learning has emerged as an effective method for dehazing images. However, data-driven deep learning
Manjun Yan, Qiuju Wu, Long Ma
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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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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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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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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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, 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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