Satellite Images Scene Classification Based Support Vector Machines and K-Nearest Neighbor


Satellite image classification is a valuable technique for producing worthy information. This paper deal with high-resolution satellite for scene classification. In this research presents three algorithms were used to extract the features which are local binary patterns, gray level co-occurrence matrix, and color histogram features. The classification process included the use of two types of data mining techniques belongs to supervisor classification which are support vector machines, and k-nearest neighbor. Test results explain that the proposed classification method obtains a very auspicious performance.