Mr. Seton Schroeder Profile

Seton Schroeder

at Pace Americas Inc

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SPIE Journal Paper | 1 May 2010

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

John Saghri, Seton Schroeder, Andrew Tescher

OE, Vol. 49, Issue 05, 057001, (May 2010) https://doi.org/10.1117/12.10.1117/1.3425656

KEYWORDS: Image compression, Matrices, Hyperspectral imaging, Image processing, Optical engineering, Imaging systems, Image classification, Receivers, Computer programming, Error analysis

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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.

Proceedings Article | 2 September 2009 Paper

An adaptive two-stage KLT scheme for spectral decorrelation in hyperspectral bandwidth compression

John Saghri, Seton Schroeder, Andrew Tescher

Proceedings Volume 7443, 744313 (2009) https://doi.org/10.1117/12.829000

KEYWORDS: Matrices, Image processing, Image compression, Hyperspectral imaging, Imaging systems, Receivers, Distortion, Error analysis, Image quality, Quality measurement

Read Abstract +

A computationally efficient adaptive 2-stage Karhunen-Loeve Transform (KLT) scheme for spectral decorrelation in hyperspectal lossy bandwidth compression is presented. The component decorrelation of the JPEG 2000 (extension 2) is replaced with the proposed adaptive 2-stage KLT spectral decorrelation scheme. Direct application of a single KLT across the entire set of hyperspectal imagery may not be computationally practical. The proposed scheme alleviates this problem by partitioning the spectral data set into small subsets. The spectral correlation within each partition is removed via the 1st-stage KLT operation. To remove the remaining inter-partition correlation, a 2nd-stage KLT is applied to the top few sets of eaui-level principal component (PC) images from the 1st-stage. The computation savings resulting from 2-stage KLT is parametrically quantified. The proposed adaptive 2-stage KLT uses only a fraction of the equi-level 1st-stage PC images in the 2nd-stage KLT process. This adaptive scheme results in reducing the size of the 2nd-stage KLT transformation matrices and further improvement in computational complexity and coding efficiency. 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 1st-stage KLT. A criterion based on the components of the eigenvectors of the cross-covariance matrix is established to identify such 1st-stage PC images. The proposed adaptive spectral decorrelation scheme also reduces the overhead bits required to transmit the covariance matrices, or eigenvectors, along the coding bit stream to the receiver through the downlink channel.

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