Low-complexity compression of multispectral images based on classified transform coding

Signal Processing: Image Communication

Volumn 21, Issue 10, 2006, Pages 850-861

  Cagnazzo, Marco ^a   Cicala, Luca ^a   Poggi, Giovanni ^a   Verdoliva, Luisa ^a  

^a UNIVERSITY OF NAPLES FEDERICO II   (Italy)

Author keywords

Image compression; Low complexity; Multispectral images; Region based coding; Remote sensing

Indexed keywords

DATA COMMUNICATION SYSTEMS; IMAGE CODING; REMOTE SENSING; SATELLITES; SPECTRUM ANALYSIS;

LOW COMPLEXITY; MULTISPECTRAL IMAGES; REGION-BASED CODING;

IMAGE COMPRESSION;

EID: 33751008636     PISSN: 09235965     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.image.2006.08.003     Document Type: Article

References (18)

1. Abousleman G.P., Marcellin M.W., and Hunt B.R. Compression of hyperspectral imagery using the 3-D DCT and hybrid DPCM/DCT. IEEE Trans. Geosci. Remote Sensing (January 1995) 26-34
2. Canta G.R., and Poggi G. Kronecker-product gain-shape vector quantization for multispectral and hyper-spectral image coding. IEEE Trans. Image Process. (May 1998) 668-678
3. Dragotti P.L., Poggi G., and Ragozini A.R.P. Compression of multispectral images by three-dimensional SPIHT algorithm. IEEE Trans. Geosci. Remote Sensing (January 2000) 416-428
4. Du Q., and Chang C. Linear mixture analysis-based compression for hyperspectral image analysis. IEEE Trans. Geosci. Remote Sensing (April 2004) 875-891
5. Gelli G., and Poggi G. Compression of multispectral images by spectral classification and transform coding. IEEE Trans. Image Process. (April 1999) 476-489
6. Gelli G., Poggi G., and Ragozini A.R.P. Multispectral-image compression based on tree-structured Markov random field segmentation and transform coding. Proceedings of the 1999 IEEE International Geoscience and Remote Sensing Symposium vol. 2 (June 1999) 1167-1170
7. Gersho A., and Gray R.M. Vector Quantization and Signal Compression (1992), Kluwer Academic Publishers, Dordrecht
8. Golub G., and van Loan C. Matrix computations. third ed. (1996), Johns Hopkins University Press, Baltimore, MD
9. Qian S.E. Hyperspectral data compression using a fast vector quantization algorithm. IEEE Trans. Geosci. Remote Sensing (August 2004) 1791-1798
10. Qian S.E., Hollinger A.B., Williams D., and Manak D. Vector quantization using spectral index-based multiple subcodebooks for hyperspectral data compression. IEEE Trans. Geosci. Remote Sensing (May 2000) 1183-1190
11. Saghri J.A., Tescher A.G., and Planinac A.M. KLT/JPEG 2000 multispectral bandwidth compression with region of interest prioritization capability. Proc. SPIE (2003) 226-235
12. Saghri J.A., Tescher A.G., and Reagan J.T. Practical transform coding of multispectral imagery. IEEE Signal Process. Mag. (January 1995) 32-43
13. Said A., and Pearlman W.A. A new, fast, and efficient image codec based on set partitioning in hierarchical trees. IEEE Trans. Circuits Systems Video Technol. (1996) 243-250
14. Shen S.S., and Kasner J.H. Effects of 3D wavelets and KLT-based JPEG-2000 hyperspectral compression on exploitation. Proc. SPIE (2000) 167-176
15. X. Tang, W.A. Pearlman, J.W. Modestino, Hyperspectral image compression using three-dimensional wavelet coding: a lossy-to-lossless solution, IEEE Trans. Geosci. Remote Sensing, submitted for publication. Available at 〈http://www.cipr.rpi.edu/∼pearlman/papers/tgrs04_tpm.pdf〉.
16. 〈http://www.kakadusoftware.com/〉.
17. 〈http://www.globalsecurity.org/space/systems/nemo.htm〉.
18. 〈http://www.cipr.rpi.edu/research/SPIHT/〉.