无人机侦察图像快速去雾算法

摘要

无人机在进行情报侦察时，容易受到不良天候条件的影响，使得侦察图像模糊不清，对比度下降，但是现有较多算法解决此类问题的实时性较差，所以本文提出了基于暗通道原理的无人机侦察图像快速去雾算法。首先对图像进行降采样，根据大气物理模型和暗通道原理，利用最小值滤波和均值滤波分析出透射率和大气光强的求解方法并进行优化，最后求解出去雾图像。通过实验验证，本文算法简单有效，实时性极高，可以用于工程实现。而且算法对图像的亮度也有一定的调整功能，具有较强的鲁棒性。%When the UAV is processing the intelligence and surveillance, it is easily affected by the bad weather, leading to the decrease of image definition and contrast. This paper raises the fast haze removal algorithm based on the dark channel of UAV reconnaissance image. Firstly, down-sampling the image and according to the physical model of atmosphere and the dark channel theory, the algorithm analyzes the method that how to do with the transmissivity and the intensity of the atmospheric light by the mini-value filtering and average filtering, and then optimizes the method. At last it receives the de-hazing image. It is proved that the algorithm is simple and effective and has the high real-time performance by a lot of experiments. It can be used for the project realization. And to a certain extent it is able to adjust the brightness of the image and is with strong robustness.