Effect Evaluation of Image Enhancement Algorithm for Power Grid Geographic Information System Based on Grey Clustering

Power grid GIS (Geographic Information System) is an important part of power informatization. It organically combines all kinds of information in power grid with graphic information reflecting geographical position, realizes a spatial database system with topological structure and analysis function, and provides a powerful means to deal with graphic and non-graphic information. As one of the most important data analysis methods in the information age, cluster analysis is widely used in data mining and knowledge discovery, pattern recognition and classification, data compression and vector quantization. In this paper, an image enhancement algorithm of power grid GIS based on grey clustering is proposed. The algorithm divides the images into blocks, and performs histogram equalization according to the information content of each image. The research results show that this method has the best image quality, and the PSNR of the image output by this method is the highest, and the entropy of the algorithm is larger and the cross entropy is smaller. The simulation results show that the proposed improved algorithm can effectively improve the clarity of the image, make the image smoother, and improve the image enhancement effect.