基于稀疏快速傅里叶的高分遥感影像压缩方法

High resolution remote sensing image compression method based on sparse fast fourier

随着高分辨率空间信息获取技术的进步及其研究成果的应用,随之而来的海量数据存储与传输的问题越来越突显。文中立足于高分遥感影像航带内必须满足一定的重叠标准要求的相邻影像间,从影像频率域数据中心对称的特点出发,进一步利用稀疏快速傅里叶提取影像中最有价值的信息即非零频点来提高压缩算法速度。并且从压缩比、压缩速度、压缩质量三方面论证了本文方法对于高分遥感影像的压缩,传输等方面有一定的应用价值。

With the progress of high - resolution spatial information acquisition technology and the discovery of its research results, the ensuing problems of mass data storage and transmission had become more and more obvious. In the paper, the sparse fast Fourier was used further to extract the most valuable information of the image to improve the algorithm speed based on the standard requirement that the high score remote sensing images between the adjacent images in flight strip must meet a certain overlap, taking the characteristics of the frequency domain image data center symmetry as the starting point. Furthermore, this method had been demonstrated that there was a certain application value of for the compression and transmission of remote sensing images from the aspects of the compression ratio, the compression speed and the compression quality.