基于支持向量机(SVM)的相关反馈算法在反馈过程中只利用SVM的分类器,反馈结果排序会出现一定错误,提出一种改进的相关反馈策略,将图像的视觉特征度量函数和SVM分类器函数进行线性加权,作为相关反馈中的相似性度量准则.实验表明,改进策略能够优化遥感图像检索排序结果,提高检索的精度.
The support vector machine (SVM)-based relevance feedback algorithm has been used in common image retrieval, but not widely applied to remote sensing images. Traditional algorithm only uses SVM classifiers, resulting in some wrong ranking sequences of retrieval results. An improved relevance feedback strategy is proposed, and it modifies the similarity measurement criterion using a weighted linear combination of feature similarity measurement and SVM classifier. Experimental results show that the proposed method improves the ranking sequence and accuracy of retrieval results.