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This paper presents an overview and evaluation of some compression algorithms suitable for remote sensing applications. Prediction\u2010based compression systems, such as DPCM and JPEG\u2010LS, and transform\u2010based compression systems, such as CCSDS\u2010IDC and JPEG\u2010XR, were tested over twenty multispectral (5\u2010band) images from CCD optical sensor of the CBERS\u20102B satellite. Performance evaluation of these algorithms was conducted using both quantitative rate\u2010distortion 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\u2010LS outperforms other lossless compression schemes, and, for lossy compression, JPEG\u2010XR can provide lower bit rate and better tradeoff between compression ratio and image quality.<\/jats:p>","DOI":"10.1155\/2012\/471857","type":"journal-article","created":{"date-parts":[[2012,4,10]],"date-time":"2012-04-10T21:01:55Z","timestamp":1334091715000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Performance Evaluation of Data Compression Systems Applied to Satellite Imagery"],"prefix":"10.1155","volume":"2012","author":[{"given":"Lilian N.","family":"Faria","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Leila M. G.","family":"Fonseca","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Max H. 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