Based on the two-dimensional distribution remote measurement system of air pollutants, this study examined the two-dimensional distribution remote measurement of pollutants by the passive imaging differential optical absorption spectroscopy technology combined with the image optimization algorithms. The concentration information of pollutants and the visual images were accurately matched using a dual-channel system that combines the ultraviolet spectra with the visual images. For the problems of the data processing of pollutants under complex backgrounds, particularly the problem that of data missing under conditions of dense smoke and obstacles, the observed values were screened and processed. Subsequently, the smoke plume diffusion model was combined with the curved cubic spline interpolation algorithm to optimize the concentration information in the entire area, and thus to quickly obtain the two-dimensional distribution image information of pollutants with high spatial resolution.