关键词: 基于内容的图像检索, 遥感图像, 五叉2/3边长分解法, 纹理特征提取

Abstract: Remote sensing image is an imagery of surface status within a certain range, which has the properties such as diversity, complexity and mass. That is why the remote sensing image retrieval is often a comparison between target image and sub images of the image database. So the remote sensing image should be decomposed before retrieval. This paper puts forward a new remote sensing image retrieval approach by using improved quintuple tree image decomposition method. First of all, the image is decomposed by improved quintuple tree image decomposition method, which splits large scale remote sensing imagery into sub images. Then texture features of each image block are extracted. Finally, the euclidean distance is computed which is between target image and sub images of the remote sensing image in the image database. These images are returned according to their euclidean distance as the final retrieval results. Aerial remote sensing images during the earthquake of Haiti are used in the experiment, which make a comparison between improved quintuple tree image decomposition method and quintuple tree image decomposition method. The improved quintuple tree image decomposition method is validated using the result of the experiment. It can accurately catch the interested sub images of the user, so a higher recall and precision can be reached.

Key words: content-based image retrieval, remote sensing images, decomposition method of quintuple 2/3 side-length, texture feature extraction