Photovoltaic power generation is impacted by the accumulation of dust on solar PV modules which leads to a reduction in efficiency. In India, soiling can lead to up to 25% losses, resulting in a total loss of 3900 MW from solar plants, equivalent to a vast field of 2.5 million panels, thus necessitating regular inspection and cleaning. This paper presents an image-processing-based approach to assess the accumulated dust for inspection and condition-monitoring purposes. The proposed approach is broadly based on qualitative and quantitative analysis carried out through image transformation and histogram feature extraction using Hellinger Distance and Earth Mover’s Distance. Dust is established as a feature that leads to deviation in pixel distribution and the resulting histogram. This deviation is expressed through a deviation matrix and a heat map. Further, a dust quantification metric is proposed based on the Earth Mover’s Distance to account for this deviation. The efficacy of the proposed methodology is demonstrated showcasing the suitability of deployment for inspection and condition-monitoring purposes.