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高光谱图像压缩技术研究进展
引用本文:万建伟,粘永健,苏令华,辛勤.高光谱图像压缩技术研究进展[J].信号处理,2010,26(9):1397-1407.
作者姓名:万建伟  粘永健  苏令华  辛勤
作者单位:国防科技大学电子科学与工程学院
基金项目:国家自然科学基金资助,武器装备预研基金资助;国防科大研究生创新基金 
摘    要:高光谱遥感已经成为遥感领域的前沿科技,在军事侦察以及国民经济中发挥着重要作用。高光谱遥感的光谱通道数达到上百个,光谱分辨率的不断提高使得高光谱图像的数据量急剧膨胀。对于星载成像光谱仪获取的高光谱图像,庞大的数据量已经给数据的存储与传输带来巨大压力,严重制约着高光谱图像的后续应用,因此,必须利用有效的压缩技术对高光谱图像进行压缩。高光谱图像压缩技术可分为无损压缩与有损压缩,在实际应用中,需要根据具体的应用需求选取不同的压缩方式。本文首先对高光谱遥感的基本概念进行了简介,然后从无损压缩与有损压缩两个方面对高光谱图像压缩技术的研究进展进行了综述,最后,指出了高光谱图像压缩技术的发展方向。 

关 键 词:高光谱遥感    无损压缩    有损压缩    质量评估
收稿时间:2009-12-31

Rearch Progress on Hyperspectral Imagery Compression Technique
WAN Jian-wei,NIAN Yong-jian,SU Ling-hua,XIN Qin.Rearch Progress on Hyperspectral Imagery Compression Technique[J].Signal Processing,2010,26(9):1397-1407.
Authors:WAN Jian-wei  NIAN Yong-jian  SU Ling-hua  XIN Qin
Affiliation:College of Electronic Science and Engineering, National Univ. of Defense Technology, Changsha
Abstract:Hyperspectral remote sensing has already become the advanced science and technology in the field of remote sensing, which plays an important function on military scout and national economy. The number of spectral channels can reach in the hundreds, with the increase of spectral resolution, the datasets of hyperspectral imagery become larger and larger. For the hyperspectral imagery acquired by imaging spectrum instrument on satellite the huge datasets have brought great press for data storage and transmission, which restricts the practical applications of hyperspectral imagery, therefore, it is necessary to compress hyperspectral imagery by efficient compression technique. The compression technique for hyperspectral imagery can lossy compression and lossless compression, For practical application, the compression type should be selected according to the application requirement. In this paper, the basic concept of hyperspectral remote sensing technique is introduced firstly, then, the research progress of hyperspectral imagery compression technique is summarized, which includes lossless compression and lossy compression. Finally, the research direction for hyperspectral imagery compression is pointed out. 
Keywords:
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