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首页> 外文期刊>Journal of Computational Methods in Sciences and Engineering >Adaptive image fog removal based on multi-scale WLS filter
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Adaptive image fog removal based on multi-scale WLS filter

机译:基于多尺度WLS滤波器的自适应图像除雾

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摘要

Atmospheric conditions induced by suspended particles, such as fog and haze, severely alter the scene appearance. In this paper, we proposed a novel adaptive defogging method based on the weighted least squares (WLS) framework, aiming at improving the image visibility under foggy or hazy weather condition. Through the inference of halo intensity and smooth degree, our method adopts image fusion technology based on multi-scale WLS filter to estimate atmospheric veil, and restores the foggy image by inverting the atmospheric scattering model. The results on the experiments of comparison with traditional algorithms demonstrate that the proposed method can achieve more accurate restoration, resulting in a great improvement in image visibility.
机译:由悬浮颗粒引起的大气条件(例如雾和霾)会严重改变场景外观。在本文中,我们提出了一种基于加权最小二乘(WLS)框架的自适应除雾方法,旨在提高在有雾或朦胧天气条件下的图像可见性。通过对晕强度和平滑度的推断,我们的方法采用基于多尺度WLS滤波器的图像融合技术来估计大气面纱,并通过反演大气散射模型来恢复模糊图像。与传统算法比较实验的结果表明,该方法可以实现更准确的还原,从而大大提高了图像的可见度。

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