Abstract
A Hyperspectral image is a sequence of images generated by collecting contiguously spaced spectral bands of data. One can view such an image sequence as a three-dimensional array of intensity values (pixels) within a rectangular prism. We present a Three-Dimensional Set Partitioned Embedded bloCK (3DSPECK) algorithm based on the observation that hyperspectral images are contiguous in the spectrum axis (this implies large interband correlations) and there is no motion between bands. Therefore, the three-dimensional discrete wavelet transform can fully exploit the inter-band correlations. A SPECK partitioning algorithm extended to three-dimensions is used to sort significant pixels. Rate distortion (Peak Signal-to-Noise Ratio (PSNR) vs. bit rate) performances were plotted by comparing 3DSPECK against 3DSPIHT on several sets of hyperspectral images. Results show that 3DSPECK is comparable to 3DSPIHT in hyperspectral image compression. 3DSPECK can achieve compression ratios in the approximate range of 16 to 27 while providing very high quality reconstructed images. It guarantees over 3 dB PSNR improvement at all rates or rate saving at least a factor of 2 over 2D coding of separate spectral bands without axial transformation.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings of SPIE - The International Society for Optical Engineering |
| Editors | B. Vasudev, T.R. Hsing, A.G. Tescher, T. Ebrahimi |
| Pages | 1037-1047 |
| Number of pages | 11 |
| Volume | 5022 II |
| DOIs | |
| State | Published - 2003 |
| Event | Image and Video Communications and Processing 2003 - Santa Clara, CA, United States Duration: Jan 21 2003 → Jan 24 2003 |
Other
| Other | Image and Video Communications and Processing 2003 |
|---|---|
| Country | United States |
| City | Santa Clara, CA |
| Period | 1/21/03 → 1/24/03 |
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Keywords
- AVIRIS imaging
- Discrete wavelet transform (DWT)
- Hyperspectral imaging
- SPIHT
- Three dimensional image compression
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Condensed Matter Physics
Cite this
Hyperspectral image compression using three-dimensional wavelet coding. / Tang, Xiaoli; Pearlman, William A.; Modestino, James W.
Proceedings of SPIE - The International Society for Optical Engineering. ed. / B. Vasudev; T.R. Hsing; A.G. Tescher; T. Ebrahimi. Vol. 5022 II 2003. p. 1037-1047.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Hyperspectral image compression using three-dimensional wavelet coding
AU - Tang, Xiaoli
AU - Pearlman, William A.
AU - Modestino, James W.
PY - 2003
Y1 - 2003
N2 - A Hyperspectral image is a sequence of images generated by collecting contiguously spaced spectral bands of data. One can view such an image sequence as a three-dimensional array of intensity values (pixels) within a rectangular prism. We present a Three-Dimensional Set Partitioned Embedded bloCK (3DSPECK) algorithm based on the observation that hyperspectral images are contiguous in the spectrum axis (this implies large interband correlations) and there is no motion between bands. Therefore, the three-dimensional discrete wavelet transform can fully exploit the inter-band correlations. A SPECK partitioning algorithm extended to three-dimensions is used to sort significant pixels. Rate distortion (Peak Signal-to-Noise Ratio (PSNR) vs. bit rate) performances were plotted by comparing 3DSPECK against 3DSPIHT on several sets of hyperspectral images. Results show that 3DSPECK is comparable to 3DSPIHT in hyperspectral image compression. 3DSPECK can achieve compression ratios in the approximate range of 16 to 27 while providing very high quality reconstructed images. It guarantees over 3 dB PSNR improvement at all rates or rate saving at least a factor of 2 over 2D coding of separate spectral bands without axial transformation.
AB - A Hyperspectral image is a sequence of images generated by collecting contiguously spaced spectral bands of data. One can view such an image sequence as a three-dimensional array of intensity values (pixels) within a rectangular prism. We present a Three-Dimensional Set Partitioned Embedded bloCK (3DSPECK) algorithm based on the observation that hyperspectral images are contiguous in the spectrum axis (this implies large interband correlations) and there is no motion between bands. Therefore, the three-dimensional discrete wavelet transform can fully exploit the inter-band correlations. A SPECK partitioning algorithm extended to three-dimensions is used to sort significant pixels. Rate distortion (Peak Signal-to-Noise Ratio (PSNR) vs. bit rate) performances were plotted by comparing 3DSPECK against 3DSPIHT on several sets of hyperspectral images. Results show that 3DSPECK is comparable to 3DSPIHT in hyperspectral image compression. 3DSPECK can achieve compression ratios in the approximate range of 16 to 27 while providing very high quality reconstructed images. It guarantees over 3 dB PSNR improvement at all rates or rate saving at least a factor of 2 over 2D coding of separate spectral bands without axial transformation.
KW - AVIRIS imaging
KW - Discrete wavelet transform (DWT)
KW - Hyperspectral imaging
KW - SPIHT
KW - Three dimensional image compression
UR - http://www.scopus.com/inward/record.url?scp=0041625899&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0041625899&partnerID=8YFLogxK
U2 - 10.1117/12.476516
DO - 10.1117/12.476516
M3 - Conference contribution
AN - SCOPUS:0041625899
VL - 5022 II
SP - 1037
EP - 1047
BT - Proceedings of SPIE - The International Society for Optical Engineering
A2 - Vasudev, B.
A2 - Hsing, T.R.
A2 - Tescher, A.G.
A2 - Ebrahimi, T.
ER -