Performance Evaluation Of Data Compression Systems Applied To Satellite Imagery

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. Copyright © 2012 Lilian N. Faria et al.Salomon, D., (2007) Data Compression: The Complete Reference, , 4th New York, NY, USA Springer(2011) CBERSChina-Brazil earth resources satellite: History, , http://www.cbers.inpe.br/?hl=encontent=historico/, National Institute For Space Research(2011) CBERSChina-Brazil earth resources satellite: Cameras, CBERS 1, 2, and 2B, , http://www.cbers.inpe.br/?hl=encontent=cameras1e2e2b/, National Institute For Space Research(2011) CBERSChina-Brazil earth resources satellite: Cameras, CBERS 3 and 4, , http://www.cbers.inpe.br/?hl=encontent=cameras3e4/, National Institute For Space ResearchGonzalez, R.C., Woods, R.E., (2007) Digital Image Processing, , 3rd New York, NY, USA Prentice HallYu, G., Vladimirova, T., Sweeting, M.N., Image compression systems on board satellites (2009) Acta Astronautica, 64 (910), pp. 988-1005Witten, I.H., Neal, R.M., Cleary, J.G., Arithmetic coding for data compression (1987) Communications of the ACM, 30 (6), pp. 520-540Huffman, D.A., A method for the construction of minimum-redundancy codes (1952) Proceedings of the Institute of Radio Engineers, 40 (9), pp. 1098-1101Golomb, S., Run-length encoding (1966) IEEE Transactions on Information Theory, 12 (3), pp. 399-401Moayeri, N., A low-complexity, fixed-rate compression scheme for color images and documents (1998) The Hewlett-Packard Journal, 50 (1), pp. 46-52Pennebaker, W.B., Mitchell, J.L., (1992) JPEG: Still Image Data Compression Standard, , 1st New York, NY, USA Springer(1997) Lossless and near-lossless coding of continuous tone still images (JPEG-LS), ISO international standardTaubman, D., Marcellin, M.W., (2001) JPEG2000: Image Compression Fundamentals, Standards and Practice, , 1st New York, NY, USA SpringerKiely, A., Klimesh, M., The ICER progressive wavelet image compressor (2003) The Interplanetary Network Progress Report, pp. 1-46. , 42155Kiely, A., Klimesh, M., Xie, H., Aranki, N., ICER-3D: A progressive wavelet-based compressor for hyperspectral images (2006) The Interplanetary Network Progress Report, pp. 1-21. , 42164(2005) CCSDS 122.0-B-1: Image data compression, report concerning space data system standards, blue book, , Consultative Committee For Space Data Systems(2007) CCSDS 120.1-G-1: Image data compression, report concerning space data system standards, green book, , Consultative Committee For Space Data SystemsITU-T Recomendation T.832 ISO/IEC 29199-2, Information technologyJPEG XR image coding systemImage coding specification, ITU-T CCITT Recommendation, 2009Dufaux, F., Sullivan, G.J., Ebrahimi, T., The JPEG XR image coding standard [Standards in a Nutshell] (2009) IEEE Signal Processing Magazine, 26 (6), pp. 195-204Tu, C., Srinivasan, S., Sullivan, G.J., Regunathan, S.L., Malvar, H.S., Low-complexity hierarchical lapped transform for lossy-to-lossless image coding in JPEG XR/HD Photo (2008) Proceedings of SPIE Applications of Digital Image Processing XXXI, 7073Introduction to DCPM encoding algorithm in data transmission sub-system of PANMUXIRMSS onboard CBERS 34 satellites, , China Academy Of Space Technology [S.l.]: CAST, (Wx CBERS03/04DPS.SM01), 2010Weinberger, M.J., Seroussi, G., Sapiro, G., The LOCO-I lossless image compression algorithm: Principles and standardization into JPEG-LS (2000) IEEE Transactions on Image Processing, 9 (8), pp. 1309-1324ITU-T T.81ISO/IEC10918-1, digital compression and coding of continuous-tone images, requirements and guidelines, ITU CCITT recommendation, September 1992(2006) CCSDS 120.0.G-2: Lossless data compression, recommendation for space data systems standards, green book, , Consultative Committee For Space Data Systems(1997) CCSDS 121.0.B-1: Lossless data compression, blue book, , Consultative Committee For Space Data SystemsYeh, P.-S., Armbruster, P., Kiely, A., Masschelein, B., Moury, G., Schaefer, C., Thiebaut, C., The new CCSDS image compression recommendation Proceedings of the IEEE Aerospace Conference March 2005, pp. 4138-4145(2011) LOCO-I/JPEG-LS reference encoderv.1.00, , http://www.hpl.hp.com/loco/software.htm/(2011) An implementation of CCSDS 122.0-B-1 recommended standard, , http://hyperspectral.unl.edu/Information technologyJPEG XR image coding systempart 5: Reference software, , [ISO/IEC JTC 1/SC 29/WG 1 N 5020], May 2011Wang, Z., Bovik, A.C., Mean squared error: Lot it or leave it? A new look at signal fidelity measures (2009) IEEE Signal Processing Magazine, 26 (1), pp. 98-117Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P., Image quality assessment: From error visibility to structural similarity (2004) IEEE Transactions on Image Processing, 13 (4), pp. 600-612Wang, Z., The SSIM index for image quality assessment, , http://www.cns.nyu.edu/lcv/ssim/(2011) Image catalog, , http://www.dgi.inpe.br/CDSR/, National Institute For Space Researc