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Journal of Electrical and Computer Engineering
Volume 2012 (2012), Article ID 471857, 15 pages
Research Article

Performance Evaluation of Data Compression Systems Applied to Satellite Imagery

1Image Processing Division, National Institute for Space Research (INPE), 12227-001 São José dos Campos, SP, Brazil
2School of Electrical and Computer Engineering, University of Campinas (Unicamp), 13083-852 Campinas, SP, Brazil

Received 30 June 2011; Revised 30 September 2011; Accepted 27 October 2011

Academic Editor: Bruno Aiazzi

Copyright © 2012 Lilian N. Faria et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Onboard image compression systems reduce the data storage and downlink bandwidth requirements in space missions. This paper presents an overview and evaluation of some compression algorithms suitable for remote sensing applications. Prediction-based compression systems, such as DPCM and JPEG-LS, and transform-based compression systems, such as CCSDS-IDC and JPEG-XR, were tested over twenty multispectral (5-band) images from CCD optical sensor of the CBERS-2B satellite. Performance evaluation of these algorithms was conducted using both quantitative rate-distortion measurements and subjective image quality analysis. The PSNR, MSSIM, and compression ratio results plotted in charts and the SSIM maps are used for comparison of quantitative performance. Broadly speaking, the lossless JPEG-LS outperforms other lossless compression schemes, and, for lossy compression, JPEG-XR can provide lower bit rate and better tradeoff between compression ratio and image quality.