| In recent years,with the rapid development of China’s aerospace,remote sensing technology,GIS and GPS technology,the monitoring technology of geographical conditions in China is developing rapidly.Geographic vector data is an important data in the monitoring of national conditions.In remote sensing images,the surface data is the largest proportion of vector data.Normally,the surface vector data obtained in the monitoring of geographical conditions is redundant,so it is necessary to simplify the surface data in remote sensing images.The existing vector contour simplification algorithm is based on vector data itself,and does not make good use of the image information in remote sensing images.Therefore,the existing vector data reduction algorithm can not well meet the requirements of the geographical condition monitoring.In order to meet the requirements of the national condition monitoring and human vision.In this paper,according to the original redundant surface terrain vector data,using the traditional simplified algorithm to obtain the initial solution.Based on the initial solution,built the search space of initial solution and based on its image feature extraction to find out the best contour to provide beautiful and practical data for operation and analysis.In this paper,three methods are used to solve this problem.1)dynamic programming algorithm.2)using multi-objective genetic algorithm for optimization.3)using the improved multi-objective particle swarm optimization algorithm.In this paper,the advantages and disadvantages of the three methods are found.Through the experimental analysis,it is found that the multi-objective particle swarm optimization algorithm and the multi-objective genetic algorithm can get better results.However,the multi-objective genetic algorithm has the defects of low efficiency and slow running speed,so the improved multi-objective particle swarm optimization algorithm is a good algorithm for the problem. |
