Abstract: For the problem of time-consuming in generating texture map, KD-tree algorithm is used to divide the data structure and reduce the complexity of KNN search algorithm. To solve the difficulty of image classification based on texture algorithm that can not accurately detect some textures with high similarity in outdoor natural scene, an improved method is proposed by adding color feature, setting the corresponding weight, and building the hybrid model. Experimental results show that the improved KNN algorithm based on KD-tree can shorten the classification time and meet the real-time requirements. The improved classification algorithm based on texture and color can obtain higher classification accuracy for the application of outdoor natural scene.