Building Extraction Algorithm for Informatized Remote Sensing Images Based on Group Intelligence

This paper enhances the accuracy of building extraction by integrating the refined Particle Swarm Optimization (PSO) method with remote sensing image (RSI) processing, particularly in intricate scenarios and surroundings undergoing substantial alterations. By adding an adaptive parameter adjustment mechanism and a local search strategy to carry out a more thorough search for the global optimal solution, this research enhances the PSO method. It preprocesses the RSIs to guarantee their quality and uses Landsat data as the remote sensing dataset. The experimental results show that the improved PSO achieves an average accuracy of 97.2% in extracting buildings from RSIs. By improving PSO and combining it with RSIs, the effectiveness of building extraction can be effectively improved.