一种超光谱图像小波压缩的基选择和评估方法  

A Wavelet Basis Selection and Evaluation Method for Hyperspectral Image Compression

作　　者：陈雷[1] 张晓林[1] 雷志东[1] 房林堂[1] 

机构地区：[1]北京航空航天大学电子信息工程学院,北京100191

出　　处：《遥测遥控》2009年第2期60-66,共7页Journal of Telemetry,Tracking and Command

基　　金：十一五装备预研项目(513060501);十五装备预研项目(41501010510);国家自然科学基金(60702012)

摘　　要：根据超光谱图像的光谱维和空间维数据具有明显差异的特性,设计一种基选择和评估方法。方法能够通过熵、编码增益、量化误差敏感度、能量集中特性、能量分布特性在不同维分别进行基的评估,并获得能与对应数据维特性匹配的最优小波基。通过对不同小波基组合压缩性能的对比实验证明,方法能够准确选择与超光谱图像特性最为匹配的小波基,从而使三维超光谱图像的小波变换获得较高的压缩性能。Since the data of spatial dimension and spectral dimension show different feature in hyperspectral images,a wavelet basis selection and evaluation method for compression of the hyperspectral images is designed.To choose the best wavelet basis for the corresponding dimension,five items which contain entropy,generalized coding gain,quantized error susceptibility,concentration property of energy and energy distribution are used to evaluate the performance of wavelet basis.Compression experiments that using different wavelet bases on spectral and spatial dimensions show that the proposed method can find the optimal wavelet bases which can match the property of hyperspectral images.And with the wavelet bases selected,three-dimensional hyperspectral image compression can gain better performance.

关 键 词：超光谱图像 小波压缩 双正交小波 广义编码增益 

分 类 号：TP751[自动化与计算机技术—检测技术与自动化装置]