Content-Based Remote Sensing Image Retrieval Using Image Multi-feature Combination and SVM-Based Relevance Feedback

摘要

In order to narrow the gap between user query concept and low-level features in content-based image retrieval, the support vector machine (SVM) based relevance feedback technique is introduced. However, remote sensing images are one kind of images with special spectral features. Relevance feedback mechanism hasn't been widely used in content-based remote sensing image retrieval (CBRSIR). Therefore, to test the effectiveness in CBRSIR, a SVM based relevance feedback algorithm based on SVM classification theory is adopted in CBRSIR to boost remote sensing image retrieval accuracy. The experimental results show that the SVM-based relevance feedback algorithm performs well in remote sensing image retrieval and has good potential in practical applications.