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    基于暗通道优先的单幅图像去雾新方法

    Improved Single Image Dehazing Using Dark Channel Prior

    • 摘要: 暗通道优先(dark channel prior)规律在处理单幅户外场景图像去雾方面取得了非常好的效果,但是该方法在处理较高分辨率图像时需消耗大量的存储和计算资源,同时对于部分场景会得到不够准确的结果.仍然基于暗通道优先,根据观察实验,得到透射梯度优先规律,并结合多分辨率处理,提出了改进的图像去雾新方法.经过大量实验和理论分析,透射梯度优先不仅显著减小了去雾处理的计算量,它所引起的优化方法和参数变化还可能提升透射图计算的准确性.实验结果也证明,新方法仅需原方法1/8左右的计算时间和存储空间,就能够得到与原方法基本一致甚至更准确的去雾结果.

       

      Abstract: The dark channel prior is a statistics of the haze-free natural outdoor images. Using dark channel prior to estimate the thickness of the haze, recent research work has made significant progresses in single image dehazing. However, it is difficult to apply existing method for processing high resolution input images because of the heavy computation costs of it. For some kinds of input images, existing method still can not reach enough accuracy which is required by visually-pleasing results. Motivated by this and based on thorough analysis of input image data, a kind of novel image prior, so-called gradient prior of transmission maps, has been proposed in this paper. Combining it with multiple-resolution image processing routine, we develop a powerful and practical single image dehazing method. The experimental results show our gradient prior of transmission maps greatly reduces the computation costs of the previous method. Furthermore, the optimization methods and parameter adjustment for our novel image prior enhance the accuracy of the computation related with transmission map, which results in better image quality under the previous method's ill-situation. Overall, compared with the state of the art, our new single image dehazing method achieves the same, and even better image quality with only around 1/8 computation time and memory cost.

       

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