An improved Bag-of-Words framework for remote sensing image retrieval in large-scale image databases

作     者：Jin Yang Jianbo Liu Qin Dai 

作者机构：Institute of Remote Sensing and Digital Earth Chinese Academy of SciencesBeijingChina University of Chinese Academy of SciencesBeijingChina 

出 版 物：《International Journal of Digital Earth》 (国际数字地球学报（英文）)

年 卷 期：2015年第8卷第4期

页      面：273-292页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Institute of Remote Sensing and Digital Earth  RADI 

主　　题：remote sensing image retrieval base image Bag-of-Words visual word 

摘      要：Due to advances in satellite and sensor technology,the number and size of Remote Sensing(RS)images continue to grow at a rapid *** continuous stream of sensor data from satellites poses major challenges for the retrieval of relevant information from those satellite *** Bag-of-Words(BoW)framework is a leading image search approach and has been successfully applied in a broad range of computer vision problems and hence has received much attention from the RS ***,the recognition performance of a typical BoW framework becomes very poor when the framework is applied to application scenarios where the appearance and texture of images are very *** this paper,we propose a simple method to improve recognition performance of a typical BoW framework by representing images with local features extracted from base *** addition,we propose a similarity measure for RS images by counting the number of same words assigned to *** compare the performance of these methods with a typical BoW *** experiments show that the proposed method has better recognition performance than that of the BoW and requires less storage space for saving local invariant features.