中文摘要：

基于内容的遥感影像检索已经成为遥感领域的研究热点,因此,本文提出了一种综合视觉词袋模型和颜色直方图的遥感影像检索方法,利用尺度不变特征算子提取影像的局部不变特征,通过视觉词袋模型组合局部特征,生成每幅影像的金字塔直方图,接着结合每幅影像的颜色直方图生成更有区分性的特征向量,利用新的特征向量集训练支持向量机分类器,通过分类器输出与查询属于一类的影像,完成遥感影像检索。试验结果表明,本文方法不仅提高了影像检索的查准率和查全率,并且验证了该方法能有效克服影像光照、噪声、方向等变化,鲁棒性较好。

英文摘要：

Content-based remote sensing image retrieval has become a research hotspot in remote sensing field. In view of this,a new method based on this bag of visual words model and color histogram is proposed for remote sensing image retrieval. The method extracts image local invariant features with scale invariant feature descriptor,combines local features by bag of visual words model,and generates pyramid histogram for each image. Then a more distinctive feature vector is achieved by combining the color histogram of each image,the support vector machine classifier is trained using the feature vector set generated last step,and the images classified into one category with the query image then to be output through the classifier. Finally remote sensing image retrieval procedures are completed.The experimental results show that the proposed method not only improves the precision and recall of image retrieval,but also verifies that the method can efficiently overcome the changes of illumination,noise and direction,and has better robustness.