Research on Multiple Classifiers Combination Method for Remote Sensing Images

Remote sensing technology is widely used in land surveying and earth science research, such as the study of the earth’s oceans, glaciers, hydrology, ecology, geology and so on, is still in the military, intelligence, commercial, economic and other aspects can also be used to select the appropriate training samples, supervised classification with five kinds of single classifier, the classification accuracy comparison of different methods. It was found that the maximum classification accuracy of the two plots was the highest with the maximum likelihood method, but the classification accuracy was not the highest for 1 of the cultivated areas. Therefore, two decision fusion based multiple classifiers combination algorithms are proposed, and the results of single classifier are processed by using ENVI and IDL software. Compared with the classification results of a single classifier, the overall classification accuracy of multiple classifiers is improved by 2.5%, and the accuracy of 1 of the cultivated land in the study area is increased by 15.5%. Methods the combination of multiple classifiers can use different characteristics of single classifier, so as to compensate for the lack of a single classifier.