Image-based air quality grade evaluation method

Abstract

The invention discloses an image-based air quality grade evaluation method, and relates to a machine learning related technology, in particular to an image processing technology. The objective of theinvention is to solve the problems of high air quality detection cost and incapability of covering each corner in a city in the prior art. The method comprises the following steps: firstly, performingHSI space conversion on an image; performing DCT transformation on the saturation channel S and the brightness channel I of the image, converting the saturation channel S and the brightness channel Iinto a frequency domain, finally, the edge pixel ratio, the high-brightness pixel ratio, the low-saturation pixel ratio and the low-frequency pixel ratio of the image are extracted to serve as features, the features are input into an SVM to be classified, and therefore an evaluation model of the air quality grade is constructed. The air quality grade evaluation model constructed by the method canaccurately estimate the air quality condition of an image acquisition place, air quality detection becomes low in cost and fine in granularity, and people can conveniently monitor the surrounding airpollution condition anytime and anywhere. And the method is more suitable for evaluating the image with moderate air humidity, rich image content and sky area proportion less than 1 / 2.

Description

technical field [0001] An image-based air quality level assessment method involves machine learning related technologies, especially image processing technology. Background technique [0002] In recent years, with the continuous advancement of my country's industrialization process and the rapid development of the country's economy, environmental pollution has also continued to intensify, and most cities have experienced different levels of pollution. Air pollution not only affects traffic and living in daily life, but also endangers our health. Therefore, daily monitoring and control of air pollution is very important. At present, the method of obtaining air quality in my country is mainly to detect and calculate the concentration of pollutants through various sophisticated instruments in monitoring stations set up in cities, and then convert it into air quality grades or indexes, and finally publish it to the Meteorological Bureau for people to inquire. However, the cost ...

AI Technical Summary

Problems solved by technology

However, due to the limitations of the selected features and machine learning methods, the methods proposed so far have shortcomings such as poor applicability or limited image acquisition locations.

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