Research of Remote Sensing Image Classification Technology Based on Multi-feature Combining and BoW Model

Authors

Li Ke, 1. The Information Engineering University, Zhengzhou 450052, China;;
You Xiong, 1. The Information Engineering University, Zhengzhou 450052, China;;
Du Lin, 1. The Information Engineering University, Zhengzhou 450052, China;;2. Troop 72515, PLA, Jinan 250014, China;

Abstract

Abstract: A new algorithm of image classification of multi feature combination and BoW model was proposed. SIFT, GIST, Census and Gabor color, and many other types of features were extracted from the images, and then through the experimental analysis to determine the best feature combination. According to the general K-means algorithm which did not consider the weight of each features, different feature component was put forward by using automatic weighted k-means algorithm, respectively SIFT, GIST, Gabor feature construct weights based on image features of vocabulary, using the soft coding algorithm for image coding, and using the SVM algorithm to complete the image classification. Experiments show that this method can effectively improve the classification accuracy of images.

Recommended Citation

Ke, Li; Xiong, You; and Lin, Du (2020) "Research of Remote Sensing Image Classification Technology Based on Multi-feature Combining and BoW Model," Journal of System Simulation: Vol. 28: Iss. 6, Article 19.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol28/iss6/19

First Page

1386

Revised Date

2015-03-02

DOI Link

https://doi.org/

Last Page

1393

CLC

P237.3

Recommended Citation

Li Ke, You Xiong, Du Lin. Research of Remote Sensing Image Classification Technology Based on Multi-feature Combining and BoW Model[J]. Journal of System Simulation, 2016, 28(6): 1386-1393.