Extraction of Aerosol Optical Extinction Properties from a Smartphone Photograph to Measure Visibility

Abstract

Airborne particulate matter participates in the scattering of light, thus leading to visibility degradation. The widespread use of smartphones provides an opportunity to determine the level of this degradation from a smartphone photograph perspective by extraction of the image features representing aerosol optical extinction properties (AOEPs). This article presents novel algorithms to measure visibility through the extraction of AOEPs (i.e., the local medium transmission rate and the local medium extinction coefficient) from a single photograph. Among them, the transmission rate is derived based on the refined photograph's dark channel prior and the extinction coefficient from the improved transmission map and depth map. Furthermore, to address the complexity of urban scenes, we draw on visual features manifested on a photograph in various weather conditions, analyze the influence of scene structures on extracted features, and identify the combination of extracted features to improve the estimated AOEPs. We also exploit the suitability of these two AOEPs and develop a method to automatically select an appropriate property from them based on the scene structure of a given photograph. The proposed algorithm is first validated through experiments using public databases. Then, two experiments, one on a city scale and the other on a national scale, are conducted using smartphone photographs crawled from the Internet to evaluate the accuracy of visibility estimation. Experimental results show that the proposed algorithms can estimate the atmospheric visibility in real time; therefore, this study provides an effective method of monitoring environments with crowdsourced data.