Research on SVM Remote Sensing Image Classification Based on Parallelization

Abstract

With the development of technology, the feature dimension and data volume of remote sensing image classification have increased rapidly. However, when remote sensing image classification based on support vector machine (SVM) is used for large-scale data calculation, there are significant limitations in training time. This paper focuses on the parallel processing method of support vector machine (SVM). Based on the popular hybrid parallel support vector machine, a hybrid parallel support vector machine based on sample cross combination is proposed, and carried on the simulation experiment analysis in the stand-alone environment.