<p>This study investigates the characteristics of dust pollution caused by open-pit mine blasting and aims to develop efficient dust reduction measures. The primary research objective is to propose a novel method for measuring dust concentration using optimized image processing techniques and to analyze the spatial and temporal distribution patterns of blasting dust pollution. A multi-level optimization method was developed for processing blasting dust images, incorporating denoising, enhancement, and segmentation techniques. Atmospheric diffusion theory was employed to calculate fixed-point dust concentrations, and function fitting methods were utilized to establish a relationship between dust concentration and gray-scale values of images. Temporal and spatial variations in dust concentration were systematically evaluated, and dust reduction measures were proposed based on these patterns. The proposed method accurately determined dust concentration at any spatio-temporal point in the blasting area, revealing four stages of temporal variation and the spatial distribution of high-concentration dust clouds. Key dust reduction measures, including water-sealed blasting and fog cannon vehicles, were designed based on the insights gained. The integration of optimized image processing and atmospheric diffusion theory enhanced the reliability and precision of dust pollution measurements. This study provides a robust methodology for measuring and analyzing dust pollution during blasting operations. The results offer valuable insights for improving worker safety and environmental quality in mining areas through the implementation of effective dust control strategies.</p>