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An Improved Single Image Haze Removal Algorithm Using Image Segmentation

机译:一种改进的基于图像分割的单图像雾度去除算法

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In this letter, we propose an improved single image haze removal algorithm using image segmentation. It can effectively resolve two common problems of conventional algorithms which are based on dark channel prior: halo artifact and wrong estimation of atmospheric light. The process flow of our algorithm is as follows. First, the input hazy image is over-segmented. Then, the segmentation results are used for improving the conventional dark channel computation which uses fixed local patches. Also, the segmentation results are used for accurately estimating the atmospheric light. Finally, from the improved dark channel and atmospheric light, an accurate transmission map is computed allowing us to recover a high quality haze-free image.
机译:在这封信中,我们提出了一种使用图像分割的改进的单图像雾度去除算法。它可以有效地解决基于暗信道先验的常规算法的两个常见问题:光晕伪影和大气光的错误估计。我们算法的处理流程如下。首先,输入的模糊图像被过度分割。然后,将分割结果用于改进使用固定局部斑块的常规暗信道计算。另外,分割结果用于准确估计大气光。最后,根据改进的暗通道和大气光,可以计算出精确的透射图,从而使我们能够恢复高质量的无雾图像。

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