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Real-time haze removal in monocular images using locally adaptive processing

机译:使用局部自适应处理实时去除单眼图像中的雾霾

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This research presents the design of a real-time system to remove the effects of haze in a sequence of monocular images. The system firstly estimates the medium transmission function from an observed hazy image using locally adaptive neighborhoods and calculation of order statistics. Next, the haze-free image is retrieved using the estimated transmission function and a physics-based restoration model. The performance of the proposed system is evaluated and compared with that of similar existing techniques in terms of objective metrics. The obtained results exhibit that the proposed system yields a higher performance in comparison with tested similar methods. Because of its high computational efficiency, the proposed system is able to operate at high rate and it is suitable for real-time applications.
机译:这项研究提出了一种实时系统的设计,以消除单眼图像序列中的雾霾影响。该系统首先使用局部自适应邻域和顺序统计计算从观察到的模糊图像中估计介质传输函数。接下来,使用估计的透射函数和基于物理的恢复模型检索无雾图像。在客观指标方面,对提出的系统的性能进行了评估,并与类似的现有技术进行了比较。获得的结果表明,与测试的类似方法相比,该系统具有更高的性能。由于其高计算效率,因此所提出的系统能够以较高的速率运行,并且适合于实时应用。

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