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An efficient method for image dehazing

机译:一种有效的图像去雾方法

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Hazy images hinder image understanding in many applications such as autonomous vehicle. In this paper, we propose an efficient method to improve image quality of hazy images. Our method estimates the transmission function based on a linear model that allows efficient computation and employs quadtree to search for a region that best represents the scatter of airlight. Experiments were conducted using publicly available images. It is demonstrated that our proposed method achieved comparable results to the state-of-the-art ones. In the estimation of sunlight radiance, the quadtree that integrates local brightness and gradient as well as spatial constraint provide a robust means to identify region of sky. Most significantly, our proposed method greatly improved the efficiency. When dealing with moderate and large size image, the improvement could be more than thirty-fold.
机译:朦胧的图像阻碍了诸如自动驾驶汽车等许多应用中的图像理解。在本文中,我们提出了一种提高模糊图像质量的有效方法。我们的方法基于线性模型估算传输函数,该模型允许高效的计算,并采用四叉树搜索最能代表空气散射的区域。实验是使用可公开获得的图像进行的。事实证明,我们提出的方法取得了与最新技术相当的结果。在估算太阳光的辐射度时,结合了局部亮度和梯度以及空间约束的四叉树为识别天空区域提供了一种可靠的方法。最重要的是,我们提出的方法大大提高了效率。当处理中等大小和大尺寸的图像时,改进幅度可能超过30倍。

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