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Single image dehazing based on detail loss compensation and degradation

机译:基于细节损失补偿和退化的单图像去雾

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Most image dehazing methods are based on the dichromatic atmospheric scattering model. However, this model cannot explain blurring effects. In this paper, we present a detail loss compensating model, based on the analysis of multiple scattering model. By assuming that the foggy image has less detail than the image captured on a clear day, we use the Laplacian template and present a smoothing point spread function to estimate the detail loss of a foggy image. The fog noise is subsequently obtained based on the estimated detail loss, and the inherent radiance of the scene can therefore be restored. Experimental results show that our method have good dehazing effect and enhance the image sharpness to a certain extent.
机译:大多数图像去雾方法都是基于双色大气散射模型。但是,该模型无法解释模糊效果。在本文中,我们在分析多重散射模型的基础上,提出了一种详细的损失补偿模型。通过假设有雾图像的细节少于在晴天拍摄的图像,我们使用拉普拉斯算子模板,并给出平滑点扩展函数来估计有雾图像的细节损失。随后基于估计的细节损失获得雾噪声,因此可以恢复场景的固有辐射度。实验结果表明,该方法具有良好的除雾效果,并在一定程度上提高了图像的清晰度。

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