基于光谱特征编码的快速矢量量化三维谱象数据压缩  

3D Hyperspectral Imagery Data Compression Using VQ with Spectral-feature-coding-Based Fast Matching

作　　者：钱神恩[1] 阎敬文[1] 孙辉[1] 张圣华 

机构地区：[1]中国科学院长春光学精密机械研究所应用光学国家重点实验室

出　　处：《电子学报》1997年第5期11-16,28,共7页Acta Electronica Sinica

基　　金：国家自然科学基金

摘　　要：本文用矢量量化技术将成象光谱仪的三维谱象数据空间景象中每一象元对应的光谱定义为一个矢量，用基于光谱特征的二进制光谱编码方法对各光谱矢量进行编码，用编码后的光谱矢量来进行快速码字匹配．这种三维谱象数据压缩方法不仅使处理速度大大加快（当码书取２５６码字时比常规的矢量量化方法快３０倍，码书取４０９６码字时快４３倍），而且压缩后恢复图象精度还有所提高．本文定义的矢量构成方法不仅可有效地保存光谱特性，而且还可充分利用成象光谱数据光谱维的相关性，可获得相当诱人的压缩比．当压缩比高达１９２：１时恢复数据仍可达到４５．２ｄＢ的峰值信噪比．In this paper we define a spectral plot corresponding to one pixel in the scene ofthe 3-dimensional data cube from an imaging spectrometer as a vector for Vector Quantization(VQ). Then each such vector is encoded into binary codes by the Spectal-Feature-Based CodingScheme (SFBCS). The codevector searching is performed with the binary codes got by the SFBCS.In this way not only the processing time is greatly sped up (30 times faster than normal VQ whenthe codebook size is 256,and 43 times faster than normal VQ when codebook size is 4096),but alsothe precision of the reconstructed data is increased. The way of constituting vectors in this papercan well preserve spectral feature,and can make good use of the correlation in spectral domain aswell. With this proposal scheme compression ratios greater than 192: 1,PSNR's of the coded hyperspectral sequences exceeding 45. 2dB can be achieved.

关 键 词：矢量量化 三维数据压缩 成象光谱 编码 

分 类 号：TN919.8[电子电信—通信与信息系统] TN911.2[电子电信—信息与通信工程]