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首页> 外文期刊>IEEE transactions on multimedia >An Iterative Image Dehazing Method With Polarization
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An Iterative Image Dehazing Method With Polarization

机译：极化的迭代图像去雾方法

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This paper presents a joint dehazing and denoising scheme for an image taken in hazy conditions. Conventional image dehazing methods may amplify the noise depending on the distance and density of the haze. To suppress the noise and improve the dehazing performance, an imaging model is modified by adding the process of amplifying the noise in hazy conditions. This model offers depth-chromaticity compensation regularization for the transmission map and chromaticity-depth compensation regularization for dehazing the image. The proposed iterative image dehazing method with polarization uses these two joint regularization schemes and the relationship between the transmission map and dehazed image. The transmission map and irradiance image are used to promote each other. To verify the effectiveness of the algorithm, polarizing images of different scenes in different days are collected. Different algorithms are applied to the original images. Experimental results demonstrate that the proposed scheme increases visibility in extreme weather conditions without amplifying the noise.
机译：本文提出了一种在朦胧条件下拍摄的图像的联合去雾和去噪方案。常规的图像去雾方法可以根据雾的距离和密度来放大噪声。为了抑制噪声并提高除雾性能，通过添加在朦胧条件下放大噪声的过程来修改成像模型。该模型为透射图提供深度色度补偿正则化，为图像除雾提供色度深度补偿正则化。提出的带极化的迭代图像去雾方法使用这两个联合正则化方案以及透射图和去雾图像之间的关系。透射图和辐照度图像用于相互促进。为了验证该算法的有效性，收集了不同日期不同场景的偏振图像。将不同的算法应用于原始图像。实验结果表明，所提出的方案在不增加噪音的情况下提高了极端天气条件下的能见度。

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