基于稀疏表达的遥感图像检索

Remote Sensing Images Retrieval Based on Sparse Representation

针对遥感图像如何快速、准确检索的问题,提出了基于稀疏表达理论的遥感图像检索新方法。该方法首先利用在线字典学习算法对查询图像和数据库图像分别训练过完备字典并将训练得到的字典作为图像的特征描述,然后利用基于特征稀疏表达的图像相似性评估算法计算查询图像与数据库图像的相似度,最后根据相似度的降序排列得到检索结果。与现有最新方法的对比实验证明了该方法的有效性。

To retrieve remote sensing images quickly and accurately , we use the online dictionary learning algorithm to train an over-complete dictionary of query images and database images respectively .The trained dic-tionary is used as an image′s feature description .Then we calculate the similarity between query image and database image with the image similarity evaluation algorithm which is based on the sparse representation of image features . Finally we retrieve the remote sensing images according to the descending order of similarity .The experimental re-sults, given in Figs.4, 5 and 6 and Table 1, and their comparison with the existing methods show preliminarily that our novel remote sensing image retrieval method based on sparse representation can accurately retrieve remote sens -ing images.