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Colorimetric Screening of the Haze Model Limits

机译:阴霾模型限制的比色筛选

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The haze model, which describes the degradation of atmospheric visibility, is a good approximation for a wide range of weather conditions and several situations. However, it misrepresents the perceived scenes and causes therefore undesirable results on dehazed images at high densities of fog. In this paper, using data from CHIC database, we investigate the possibility to screen the regions of the hazy image, where the haze model inversion is likely to fail in providing perceptually recognized colors. This study is done upon the perceived correlation between the atmospheric light color and the objects' colors at various fog densities. Accordingly, at high densities of fog, the colors are badly recovered and do not match the original fog-free image. At low fog densities, the haze model inversion provides acceptable results for a large panel of colors.
机译:描述了大气可视性降低的雾度模型是各种天气条件和几种情况的良好近似。然而,它歪曲了感知的场景,因此在高密度的雾中的去除湿图像上的不良结果。在本文中,使用别致数据库的数据,我们调查筛选朦胧图像区域的可能性,其中雾度模型反转可能在提供感知识别的颜色方面失败。本研究是在各种雾密度下的大气浅色和物体颜色之间的感知相关性。因此,在高密度的雾密度下,颜色恢复严重恢复并且不匹配原始的无雾图像。在低雾密度下,雾度模型反演为大号颜色提供可接受的结果。

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