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An Improved Dehazing Algorithm Of Aerial High-Definition Image

机译:一种改进的空中清晰度图像脱落算法

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For unmanned aerial vehicle(UAV) images, the sensor can not get high quality images due to fog and haze weather. To solve this problem, An improved dehazing algorithm of aerial high-definition image is proposed. Based on the model of dark channel prior, the new algorithm firstly extracts the edges from crude estimated transmission map and expands the extracted edges. Then according to the expended edges, the algorithm sets a threshold value to divide the crude estimated transmission map into different areas and makes different guided filter on the different areas compute the optimized transmission map. The experimental results demonstrate that the performance of the proposed algorithm is substantially the same as the one based on dark channel prior and guided filter. The average computation time of the new algorithm is around 40% of the one as well as the detection ability of UAV image is improved effectively in fog and haze weather.
机译:对于无人驾驶飞行器(UAV)图像,传感器由于雾和阴霾天气而无法获得高质量的图像。为了解决这个问题,提出了一种改进的天线高清图像脱落算法。基于暗信道的模型,新算法首先从粗估的透射映射中提取边缘并扩展提取的边缘。然后根据消费边缘,算法将阈值设置为将粗估估计的传输映射划分为不同的区域,并在不同区域对不同的引导滤波器计算优化的传输映射。实验结果表明,所提出的算法的性能与基于暗信道先前和引导滤波器的性能基本相同。新算法的平均计算时间占据了大约40%的,并且在雾和阴霾天气中有效地提高了UAV图像的检测能力。

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