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HazeRD: An outdoor scene dataset and benchmark for single image dehazing

机译:HazaRD:室外场景数据集和单个图像去雾的基准

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In this paper, a new dataset, HazeRD, is proposed for benchmarking dehazing algorithms under more realistic haze conditions. HazeRD contains fifteen real outdoor scenes, for each of which five different weather conditions are simulated. As opposed to prior datasets that made use of synthetically generated images or indoor images with unrealistic parameters for haze simulation, our outdoor dataset allows for more realistic simulation of haze with parameters that are physically realistic and justified by scattering theory. All images are of high resolution, typically six to eight megapixels. We test the performance of several state-of-the-art dehazing techniques on HazeRD. The results exhibit a significant difference among algorithms across the different datasets, reiterating the need for more realistic datasets such as ours and for more careful benchmarking of the methods.
机译:在本文中,提出了一个新的数据集HazeRD,用于在更现实的雾度条件下对除雾算法进行基准测试。 HazeRD包含15个真实的室外场景,针对每个场景模拟了5种不同的天气情况。与使用合成图像或具有不真实参数的室内图像进行雾度模拟的现有数据集相反,我们的室外数据集允许使用物理上真实且经散射理论证明合理的参数对雾度进行更真实的模拟。所有图像都是高分辨率的,通常为六到八百万像素。我们在HazeRD上测试了几种最先进的除雾技术的性能。结果显示出不同数据集之间算法之间的显着差异,重申了对更现实的数据集(例如我们的数据集)以及更仔细地对方法进行基准测试的需求。

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