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Lossy compression of hyperspectral images by using Enhanced Multivariance Products Representation (EMPR) method

机译:使用增强的多种程度产品表示(EMPR)方法,使用增强的多种度产品表示(EMPR)方法的损坏压缩

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摘要

In preceding paper, a compression algorithm for hyperspectral images using a novel multivariate data decomposition method called Enhanced Multivariance Products Representation (EMPR) is developed. The test results obtained by performing some EMPR approximations of different orders and their qualities are reported. In order to improve performance, EMPR approach is applied to high-subband of hyperspectral data which is spectrally decorrelated using Haar wavelet transform. Low subbands are losslessly compressed using JPEG2000 Proposed methods are tested with AVIRIS data, promising compression vs. Peak-Signal-to-Noise Ratios (PSNR) are obtained.
机译:在前面的纸张中,开发了一种使用称为增强多功能产品表示(EMPR)的新型多变量数据分解方法的高光谱图像的压缩算法。报告了通过执行一些不同订单及其质量的EMPR近似获得的测试结果。为了提高性能,将EMPR方法应用于高光谱数据的高子带,其使用HAAR小波变换频谱去相关。使用JPEG2000无损压缩的低子带是用Aviris数据测试的,获得有前景的压缩与峰值信噪比(PSNR)。

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