Lossless hyperspectral image compression using wavelet transform based spectral decorrelation

Behcet Ugur Toreyin; Ozan Yilmaz; Yakup Murat Mert; Fethi Turk

doi:10.1109/RAST.2015.7208350

Lossless hyperspectral image compression using wavelet transform based spectral decorrelation

Behcet Ugur Toreyin, Ozan Yilmaz, Yakup Murat Mert, Fethi Turk

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

12 Citations (Scopus)

Abstract

Integer-coefficient Discrete Wavelet Transformation (DWT) filters widely used in the literature are implemented and investigated as spectral decorrelator. 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 computational complexity and CR. 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. Two-dimensional images corresponding to each band is compressed using JPEG-LS algorithm. 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 onboard lossless hyperspectral image compression.

Original language	English
Title of host publication	RAST 2015 - Proceedings of 7th International Conference on Recent Advances in Space Technologies
Editors	M. Fevzi Unal, Suleyman Basturk, Okyay Kaynak, Abdurrahman Hacioglu, Fuat Ince
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	251-254
Number of pages	4
ISBN (Electronic)	9781467377607
DOIs	https://doi.org/10.1109/RAST.2015.7208350
Publication status	Published - 17 Aug 2015
Externally published	Yes
Event	7th International Conference on Recent Advances in Space Technologies, RAST 2015 - Istanbul, Turkey Duration: 16 Jun 2015 → 19 Jun 2015

Publication series

Name	RAST 2015 - Proceedings of 7th International Conference on Recent Advances in Space Technologies

Conference

Conference	7th International Conference on Recent Advances in Space Technologies, RAST 2015
Country/Territory	Turkey
City	Istanbul
Period	16/06/15 → 19/06/15

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Keywords

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

Access to Document

10.1109/RAST.2015.7208350

Cite this

Toreyin, B. U., Yilmaz, O., Mert, Y. M., & Turk, F. (2015). Lossless hyperspectral image compression using wavelet transform based spectral decorrelation. In M. F. Unal, S. Basturk, O. Kaynak, A. Hacioglu, & F. Ince (Eds.), RAST 2015 - Proceedings of 7th International Conference on Recent Advances in Space Technologies (pp. 251-254). Article 7208350 (RAST 2015 - Proceedings of 7th International Conference on Recent Advances in Space Technologies). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/RAST.2015.7208350

Toreyin, Behcet Ugur ; Yilmaz, Ozan ; Mert, Yakup Murat et al. / Lossless hyperspectral image compression using wavelet transform based spectral decorrelation. RAST 2015 - Proceedings of 7th International Conference on Recent Advances in Space Technologies. editor / M. Fevzi Unal ; Suleyman Basturk ; Okyay Kaynak ; Abdurrahman Hacioglu ; Fuat Ince. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 251-254 (RAST 2015 - Proceedings of 7th International Conference on Recent Advances in Space Technologies).

@inproceedings{c2cb000571c84eb7ad1c7bbef46b02a0,

title = "Lossless hyperspectral image compression using wavelet transform based spectral decorrelation",

abstract = "Integer-coefficient Discrete Wavelet Transformation (DWT) filters widely used in the literature are implemented and investigated as spectral decorrelator. 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 computational complexity and CR. 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. Two-dimensional images corresponding to each band is compressed using JPEG-LS algorithm. 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 onboard lossless hyperspectral image compression.",

keywords = "AVIRIS images, hyperspectral data compression, hyperspectral imagery, integer-coefficient wavelet transforms, JPEG-LS, lossless compression, on-board compression schemes, spectral decorrelation",

author = "Toreyin, {Behcet Ugur} and Ozan Yilmaz and Mert, {Yakup Murat} and Fethi Turk",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 7th International Conference on Recent Advances in Space Technologies, RAST 2015 ; Conference date: 16-06-2015 Through 19-06-2015",

year = "2015",

month = aug,

day = "17",

doi = "10.1109/RAST.2015.7208350",

language = "English",

series = "RAST 2015 - Proceedings of 7th International Conference on Recent Advances in Space Technologies",

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Toreyin, BU, Yilmaz, O, Mert, YM & Turk, F 2015, Lossless hyperspectral image compression using wavelet transform based spectral decorrelation. in MF Unal, S Basturk, O Kaynak, A Hacioglu & F Ince (eds), RAST 2015 - Proceedings of 7th International Conference on Recent Advances in Space Technologies., 7208350, RAST 2015 - Proceedings of 7th International Conference on Recent Advances in Space Technologies, Institute of Electrical and Electronics Engineers Inc., pp. 251-254, 7th International Conference on Recent Advances in Space Technologies, RAST 2015, Istanbul, Turkey, 16/06/15. https://doi.org/10.1109/RAST.2015.7208350

Lossless hyperspectral image compression using wavelet transform based spectral decorrelation. / Toreyin, Behcet Ugur; Yilmaz, Ozan; Mert, Yakup Murat et al.
RAST 2015 - Proceedings of 7th International Conference on Recent Advances in Space Technologies. ed. / M. Fevzi Unal; Suleyman Basturk; Okyay Kaynak; Abdurrahman Hacioglu; Fuat Ince. Institute of Electrical and Electronics Engineers Inc., 2015. p. 251-254 7208350 (RAST 2015 - Proceedings of 7th International Conference on Recent Advances in Space Technologies).

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

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AU - Toreyin, Behcet Ugur

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AU - Mert, Yakup Murat

AU - Turk, Fethi

PY - 2015/8/17

Y1 - 2015/8/17

N2 - Integer-coefficient Discrete Wavelet Transformation (DWT) filters widely used in the literature are implemented and investigated as spectral decorrelator. 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 computational complexity and CR. 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. Two-dimensional images corresponding to each band is compressed using JPEG-LS algorithm. 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 onboard lossless hyperspectral image compression.

AB - Integer-coefficient Discrete Wavelet Transformation (DWT) filters widely used in the literature are implemented and investigated as spectral decorrelator. 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 computational complexity and CR. 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. Two-dimensional images corresponding to each band is compressed using JPEG-LS algorithm. 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 onboard lossless hyperspectral image compression.

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ER -

Toreyin BU, Yilmaz O, Mert YM, Turk F. Lossless hyperspectral image compression using wavelet transform based spectral decorrelation. In Unal MF, Basturk S, Kaynak O, Hacioglu A, Ince F, editors, RAST 2015 - Proceedings of 7th International Conference on Recent Advances in Space Technologies. Institute of Electrical and Electronics Engineers Inc. 2015. p. 251-254. 7208350. (RAST 2015 - Proceedings of 7th International Conference on Recent Advances in Space Technologies). doi: 10.1109/RAST.2015.7208350

Lossless hyperspectral image compression using wavelet transform based spectral decorrelation

Abstract

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Bibliographical note

Keywords

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