基于光学成像的空气质量定性判定方法

A methodof air quality qualitative judgement based on optical imaging

针对我国目前气象观测站点分散不均匀导致实时得到的空气质量信息不准确的问题,文中提出一种基于光学成像的空气质量定期性制定方法。该文结合通过数字图像去雾领域中基于光学成像原理去雾得到的大气透射率和通过气象观测领域中得到的空气质量与散射系数间的相关性,并考量同一景深下大气透射率和散射系数之间的指数关系,利用BP神经网络模型学习空气质量和图片透射率间的隐性联系,做到通过图片来定性判定其空气质量。实验结果显示,所提空气质量判定方法的整体识别率为83.72%,优类和良类识别率达到了90%以上。

As the real-time information of air quality is inaccurate due to the uneven distribution of meteorological observation stations in China, a method of air quality qualitative judgement method based on optical imaging is proposed. The atmospheric transmittance obtained by defogging based on optical imaging principle in the digital image defogging domain,and the correlation between air quality and scattering coefficient obtained by meteorological observation are combined in this paper.And also,the exponential relationship between the atmospheric transmittance and the scattering coefficient at the same depth of field is considered,and the implicit relation between air quality and image transmittance is studied by means of BP neural network model. On the bsasis of the above method,the air quality is judged qualitatively by pictures. The experimental results show that the overall recognition rate of the proposed air quality judgement method is 83.72%,in which the recognition rate of superior and good classes is over 90%.