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Adaptive two-stage Karhunen-Loeve-transform scheme for spectral decorrelation in hyperspectral bandwidth compression

机译:高光谱带宽压缩中频谱去相关的自适应两阶段Karhunen-Loeve变换方案

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摘要

A computationally efficient adaptive two-stage Karhunen-Loeve transform (KLT) scheme for spectral decorrelation in hyperspectral lossy bandwidth compression is presented. The component decorrelation of the JPEG 2000 (extension 2) is replaced with an adaptive two-stage KLT scheme. The data are partitioned into small subsets. The spectral correlation within each partition is removed via a first-stage KLT. The interpartition spectral correlation is removed using a second-stage KLT applied to the resulting top few sets of equilevel principal component (PC) images. Since only a fraction of each equilevel first-stage PC images are used in the second stage, the KLT transformation matrices will have smaller sizes, leading to further improvement in computational complexity and coding efficiency. The computation of the proposed approach is parametrically quantified. It is shown that reconstructed image quality, as measured via statistical and/or machine-based exploitation measures, is improved by using a smaller partition size in the first-stage KLT. A criterion based on the components of the eigenvectors of the cross-covariance matrix is established to select first-stage PC images, which are used in the second-stage KLT. The proposed scheme also reduces the overhead bits required to transmit the covariance information to the receiver in conjunction with the coding bitstream.
机译:提出了一种高效的自适应两阶段Karhunen-Loeve变换(KLT)方案,用于高光谱有损带宽压缩中的频谱去相关。 JPEG 2000(扩展名2)的组件去相关被自适应两阶段KLT方案取代。数据被分成小的子集。每个分区内的光谱相关性通过一级KLT消除。使用第二阶段KLT去除分区间的光谱相关性,该第二阶段的KLT应用于生成的等量主成分(PC)图像的前几组。由于在第二阶段仅使用每个等值的第一阶段PC图像的一小部分,因此KLT变换矩阵的大小将更小,从而进一步提高了计算复杂度和编码效率。所提出方法的计算是参数化的。结果表明,通过在第一阶段KLT中使用较小的分区大小,可以改善通过统计和/或基于机器的开发措施所测量的重建图像质量。建立基于互协方差矩阵特征向量成分的标准,以选择用于第二阶段KLT的第一阶段PC图像。所提出的方案还减少了与编码比特流一起将协方差信息发送到接收机所需的开销比特。

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