RGB Image-Based Retrieval of Extinction Coefficients and Ångström Exponent for Fog Characterization

Fog is a meteorological phenomenon that significantly impacts traffic safety and public health. However, real-time monitoring remains challenging due to the spatially sparse distribution of dedicated observation networks. This is particularly problematic given the highly localized nature of fog formation. This study proposes an RGB image-based method to derive fog optical properties—specifically the extinction coefficient at three visible wavelengths (R:597nm, G:534nm, B:459nm) and the Ångström exponent (AE)— from pixel intensity differences of objects located at known distances. To support the observational analysis, we simulated extinction coefficients and AE based on a modified gamma distribution as a fog size distribution model. Simulation results showed that as fog particle size increases, the AE decreases toward zero or negative values. This is accompanied by an inversion of the wavelength-dependent extinction coefficient, where scattering at longer (red) wavelengths exceeds that at shorter (blue) wavelengths. These theoretical findings were consistent with observations from six fog events captured at 2-minute intervals during each event, between December 2021 and March 2023 in Daejeon, South Korea. When fog was present, the extinction coefficient increased and AE approached zero or negative values. Fog dissipation was marked by decreasing extinction coefficients and a recovery of AE toward positive values. An R/B extinction coefficient ratio greater than 1 was identified as a generally reliable indicator of fog presence. Direct RGB images based optical observations confirmed these findings across all six fog events. This approach offers a cost-effective and scalable alternative for fog monitoring using widely available imaging sources such as CCTVs.