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Proceedings ArticleDOI

Evaluation of on-board integer wavelet transform based spectral decorrelation schemes for lossless compression of hyperspectral images

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TLDR
Results suggest that Cohen-Daubechies-Feauveau (CDF) 9/7 integer-coefficient wavelet transform with five levels of spectral subband decomposition would be an efficient spectral decorrelator for on-board lossless hyperspectral image compression.
Abstract
Integer-coefficient Discrete Wavelet Transformation (DWT) filters widely used in the literature are implemented and investigated as spectral decorrelator for on-board lossless hyperspectral image compression. As the performance of spectral decorrelation step has direct impact on the compression ratio (CR), it is important to employ the most convenient spectral decorrelator in terms of low computational complexity and high CR. Extensive tests using AVIRIS image data set are carried out and CRs corresponding to various subband decomposition levels are presented within a lossless hyperspectral compression framework. Results suggest that Cohen-Daubechies-Feauveau (CDF) 9/7 integer-coefficient wavelet transform with five levels of spectral subband decomposition would be an efficient spectral decorrelator for on-board lossless hyperspectral image compression.

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Citations
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GPU Acceleration of Clustered DPCM for Lossless Compression of Hyperspectral Images

TL;DR: This paper presents a parallel implementation of the C-DPCM algorithm on graphics processing units (GPUs) with the compute unified device architecture, which is a parallel computing platform and programming model developed by NVIDIA.
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Iterative Enhanced Multivariance Products Representation for Effective Compression of Hyperspectral Images

TL;DR: An efficient lossy HS image compression method based on enhanced multivariance products representation (EMPR) is proposed and it is observed that both higher peak signal-to-noise ratio values and improved classification accuracy are achieved from EMPR-based methods.
Journal ArticleDOI

Development of computationally efficient biorthogonal wavelets.

TL;DR: This research develops a formula for wavelets (which can be implemented with bitwise shifts and additions) that are derived from these two wavelets and develops a formulation for computationally efficient wavelet prediction (P) and update (U) filters of two-channel lifting structures.
Proceedings ArticleDOI

Spectral decorrelation of hyperspectral imagery using fractional wavelet transform

TL;DR: A fractional wavelet transform based method is introduced for spectral decorrelation of hyperspectral data and performance results pertaining to AVIRIS datasets are presented in comparison with existing regular wavelet decomposition based compression methods.
References
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Journal ArticleDOI

Reversible integer-to-integer wavelet transforms for image compression: performance evaluation and analysis

TL;DR: At low bit rates, reversible integer-to-integer and conventional versions of transforms were found to often yield results of comparable quality, with the best choice for a given application depending on the relative importance of the preceding criteria.
Proceedings ArticleDOI

Lossless image compression using integer to integer wavelet transforms

TL;DR: This work presents an approach to build integer to integer wavelet transforms based upon the idea of factoring wavelet transformations into lifting steps, which allows the construction of an integer version of every wavelet transform.