基于暗通道先验的航拍图像去雾效果优化

Fog removal effect optimization of aerial image based on dark channel prior

航拍图像数据量大、图幅多、云雾情况复杂,在观测了大量航拍去雾图像后,发现效果并不理想,对比度依旧不高。通过研究暗通道先验去雾算法,分析有雾图像退化过程,提出了基于暗通道先验的航拍图像去雾效果优化方法。当原始图像云雾不均时,采用增强大气透射率图层对比度的方法来改善去雾输出图像的质量;此外,针对全部有雾输入图像,使用自动对比度或自动颜色增强的图像处理方法来提升去雾输出图像的亮度;最后通过计算机编码实现优化算法进行实验,采用无参考的客观图像质量评价方法对优化前后的图像效果量化评价。分析结果表明,在保障运算时间的基础上,优化算法使输出的去雾图像效果更加清晰,符合无人机航拍图像数据质量控制的要求。

After observing a large number of aerial images,it is found that the effect is not ideal and the contrast is still not high.In this paper,through the study of the dark channel prior defogging algorithm,the process of fog image degradation is analyzed,and an aerial image defogging effect optimization method based on the dark channel prior is proposed.When the original image is uneven,the method of enhancing the contrast of atmospheric transmittance layer is used to improve the quality of the output image.In addition,for all the input images with fog,an image processing method of automatic contrast or automatic color enhancement is used to enhance the brightness of the output image.The optimization algorithm uses the objective image quality evaluation method without reference to evaluating the image effect before and after optimization.The analytical results show that,on the basis of ensuring the operation time,the optimized algorithm makes the output defog image more clear and meets the requirements of UAV aerial image data quality control.