Algorithm Development of a Visibility Monitoring Technique Using Digital Image Analysis

Abstract

Atmospheric visibility is one of the indicators used to evaluate the status of air quality. Based on a conceptual definition of visibility as the maximum distance at which the outline of the selected target can be recognized, an image analysis technique is introduced here and an algorithm is developed for visibility monitoring. Although there are various measurement techniques, ranging from bulk and precise instruments to naked eye observation techniques, each has their own limitations. In this study, a series of image analysis techniques were introduced and examined for in-situ application. An imaging system was built up using a digital camera and was installed on the study sites in Incheon and Seoul separately. Visual range was also monitored by using a dual technology visibility sensor in Incheon and transmissometer in Seoul simultaneously. The Sobel mask filter was applied to detect the edge lines of objects by extracting the high frequency from the digital image. The root mean square (RMS) index of variation among the pixels in the image was substantially correlated with the visual ranges in Incheon and Seoul with correlations of <TEX>$R^2$</TEX>=0.88 and <TEX>$R^2$</TEX>=0.71, respectively. The regression line equations between the visual range and the RMS index in Incheon and Seoul were VR=<TEX>$2.36e^{0.46{\times}(RMS)}$</TEX> and VR=<TEX>$3.18e^{0.15{\times}(RMS)}$</TEX>, respectively. It was also confirmed that the fine particles (<TEX>$PM_{2.5}$</TEX>) have more impacts to the impairment of visibility than coarse particles.