Image Contrast Soiling Loss Quantification with Multiple Dust Types

• Image contrast relationship valid and similar for various common dust types. • Slope of linear regression becomes steep for light-absorbing dust types. • Image contrast model assumption validated with experimental data. The image contrast method is a potentially viable approach for quantifying soiling loss. It involves imaging a surface with intrinsic contrast and applying a mathematical model that correlates the image’s black-to-white ratio with the angle-corrected normal-incidence soiling loss. This method had previously been tested with one type of dust. The objective of this study was to assess the method’s general validity across multiple dust types. Experiments were conducted to measure normal-incidence soiling loss and to capture images of soiling samples over a checker pattern. Histogram data of the images were used to determine the model parameters for each dust type. Using these parameters, the camera-angle-corrected normal-incidence soiling loss could be modeled from the black-to-white ratio, and the model’s predictions agreed closely with the experimental measurements. The findings suggest that the image contrast method can be applied to various dust types and, therefore, can be utilized in different regions around the world.