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

Behçet Uǧur Töreyin; Ozan Yilmaz; Yakup Murat Mert

doi:10.1109/WHISPERS.2014.8077562

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

Behçet Uǧur Töreyin, Ozan Yilmaz, Yakup Murat Mert

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Citations (Scopus)

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.

Original language	English
Title of host publication	2014 6th Workshop on Hyperspectral Image and Signal Processing
Subtitle of host publication	Evolution in Remote Sensing, WHISPERS 2014
Publisher	IEEE Computer Society
ISBN (Electronic)	9781467390125
DOIs	https://doi.org/10.1109/WHISPERS.2014.8077562
Publication status	Published - 28 Jun 2014
Externally published	Yes
Event	6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2014 - Lausanne, Switzerland Duration: 24 Jun 2014 → 27 Jun 2014

Publication series

Name	Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing
Volume	2014-June
ISSN (Print)	2158-6276

Conference

Conference	6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2014
Country/Territory	Switzerland
City	Lausanne
Period	24/06/14 → 27/06/14

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

Keywords

AVIRIS images
hyperspectral data compression
hyperspectral imagery
integer-coefficient wavelet transforms
lossless compression
on-board compression schemes
spectral decorrelation

Access to Document

10.1109/WHISPERS.2014.8077562

Cite this

Töreyin, B. U., Yilmaz, O., & Mert, Y. M. (2014). Evaluation of on-board integer wavelet transform based spectral decorrelation schemes for lossless compression of hyperspectral images. In 2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2014 Article 8077562 (Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing; Vol. 2014-June). IEEE Computer Society. https://doi.org/10.1109/WHISPERS.2014.8077562

Töreyin, Behçet Uǧur ; Yilmaz, Ozan ; Mert, Yakup Murat. / Evaluation of on-board integer wavelet transform based spectral decorrelation schemes for lossless compression of hyperspectral images. 2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2014. IEEE Computer Society, 2014. (Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing).

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

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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Töreyin, BU, Yilmaz, O & Mert, YM 2014, Evaluation of on-board integer wavelet transform based spectral decorrelation schemes for lossless compression of hyperspectral images. in 2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2014., 8077562, Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing, vol. 2014-June, IEEE Computer Society, 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2014, Lausanne, Switzerland, 24/06/14. https://doi.org/10.1109/WHISPERS.2014.8077562

Evaluation of on-board integer wavelet transform based spectral decorrelation schemes for lossless compression of hyperspectral images. / Töreyin, Behçet Uǧur; Yilmaz, Ozan; Mert, Yakup Murat.
2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2014. IEEE Computer Society, 2014. 8077562 (Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing; Vol. 2014-June).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Töreyin BU, Yilmaz O, Mert YM. Evaluation of on-board integer wavelet transform based spectral decorrelation schemes for lossless compression of hyperspectral images. In 2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2014. IEEE Computer Society. 2014. 8077562. (Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing). doi: 10.1109/WHISPERS.2014.8077562

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

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