{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:15:19Z","timestamp":1760242519376,"version":"build-2065373602"},"reference-count":23,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2017,9,21]],"date-time":"2017-09-21T00:00:00Z","timestamp":1505952000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Hyperspectral imaging is a technology which, by sensing hundreds of wavelengths per pixel, enables fine studies of the captured objects. This produces great amounts of data that require equally big storage, and compression with algorithms such as the Consultative Committee for Space Data Systems (CCSDS) 1.2.3 standard is a must. However, the speed of this lossless compression algorithm is not enough in some real-time scenarios if we use a single-core processor. This is where architectures such as Field Programmable Gate Arrays (FPGAs) and Graphics Processing Units (GPUs) can shine best. In this paper, we present both FPGA and OpenCL implementations of the CCSDS 1.2.3 algorithm. The proposed paralellization method has been implemented on the Virtex-7 XC7VX690T, Virtex-5 XQR5VFX130 and Virtex-4 XC2VFX60 FPGAs, and on the GT440 and GT610 GPUs, and tested using hyperspectral data from NASA\u2019s Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS). Both approaches fulfill our real-time requirements. This paper attempts to shed some light on the comparison between both approaches, including other works from existing literature, explaining the trade-offs of each one.<\/jats:p>","DOI":"10.3390\/rs9100973","type":"journal-article","created":{"date-parts":[[2017,9,21]],"date-time":"2017-09-21T12:17:40Z","timestamp":1505996260000},"page":"973","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Parallel Implementation of the CCSDS 1.2.3 Standard for Hyperspectral Lossless Compression"],"prefix":"10.3390","volume":"9","author":[{"given":"Daniel","family":"B\u00e1scones","sequence":"first","affiliation":[{"name":"Complutense University of Madrid, Department of Computer Architecture and Automatics, Computer Science Faculty, Complutense University of Madrid, 28040 Madrid, Spain"}]},{"given":"Carlos","family":"Gonz\u00e1lez","sequence":"additional","affiliation":[{"name":"Complutense University of Madrid, Department of Computer Architecture and Automatics, Computer Science Faculty, Complutense University of Madrid, 28040 Madrid, Spain"}]},{"given":"Daniel","family":"Mozos","sequence":"additional","affiliation":[{"name":"Complutense University of Madrid, Department of Computer Architecture and Automatics, Computer Science Faculty, Complutense University of Madrid, 28040 Madrid, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2017,9,21]]},"reference":[{"key":"ref_1","unstructured":"Leighton, F.T. (2014). Introduction to Parallel Algorithms and Architectures: Arrays Trees Hypercubes, Elsevier."},{"key":"ref_2","first-page":"202","article-title":"The free lunch is over: A fundamental turn toward concurrency in software","volume":"30","author":"Sutter","year":"2005","journal-title":"Dr. Dobb\u2019s J."},{"key":"ref_3","unstructured":"Chang, C.-I. (2003). Hyperspectral Imaging: Techniques for Spectral Detection and Classification, Springer."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"546","DOI":"10.1109\/36.581964","article-title":"The lossless compression of AVIRIS images by vector quantization","volume":"35","author":"Ryan","year":"1997","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"416","DOI":"10.1109\/36.823937","article-title":"Compression of multispectral images by three-dimensional SPIHT algorithm","volume":"38","author":"Dragotti","year":"2000","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1109\/LGRS.2005.859942","article-title":"Progressive 3-D coding of hyperspectral images based on JPEG 2000","volume":"3","author":"Penna","year":"2006","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Motta, G., Rizzo, F., and Storer, J.A. (2006). Hyperspectral Data Compression, Springer.","DOI":"10.1007\/0-387-28600-4"},{"key":"ref_8","unstructured":"(2017, September 19). Lossless Multispectral & Hyperspectral Image Compression. Available online: https:\/\/public.ccsds.org\/Pubs\/120x2g1.pdf."},{"key":"ref_9","unstructured":"(2017, September 19). Lossless Multispectral & Hyperspectral Image Compression. Available online: https:\/\/public.ccsds.org\/Pubs\/123x0b1ec1.pdf."},{"key":"ref_10","unstructured":"(2017, September 19). AVIRIS-NG Website, Available online: https:\/\/aviris-ng.jpl.nasa.gov\/."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"757","DOI":"10.1109\/JSTARS.2015.2497163","article-title":"Multispectral and Hyperspectral Lossless Compressor for Space Applications (HyLoC): A Low-Complexity FPGA Implementation of the CCSDS 1.2.3 Standard","volume":"9","author":"Santos","year":"2016","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_12","unstructured":"Keymeulen, D., Luong, H., Pham, T., Ghossemi, H., Shin, S., Kiely, A., Klimesh, M., Cheng, M., Dolman, D., and Holyoake, C. (2016, January 28\u201329). FPGA Implementation of Space-Based Lossless and Lossy Multispectral and Hyperspectral Image Compression. Proceedings of the 5th International Workshop on On-Board Payload Data Compression, Frascati, Italy."},{"key":"ref_13","unstructured":"Theodorou, G., Kranitis, N., Tsigkanos, A., and Paschalis, A. (2016, January 28\u201329). High Performance CCSDS 123.0-B-1 Multispectral & Hyperspectral Image Compression Implementation on a Space-Grade SRAM FPGA. Proceedings of the 5th International Workshop on On-Board Payload Data Compression, Frascati, Italy."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Keymeulen, D., Aranki, N., Bakhshi, A., Luong, H., Sarture, C., and Dolman, D. (2014, January 14\u201317). Airborne demonstration of FPGA implementation of Fast Lossless hyperspectral data compression system. Proceedings of the 2014 NASA\/ESA Conference on Adaptive Hardware and Systems (AHS), Leicester, UK.","DOI":"10.1109\/AHS.2014.6880188"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Lopez, G., Napoli, E., and Strollo, A.G. (2015, January 24\u201327). FPGA implementation of the CCSDS-123.0-B-1 lossless Hyperspectral Image compression algorithm prediction stage. Proceedings of the 2015 IEEE 6th Latin American Symposium on Circuits & Systems (LASCAS), Montevideo, Uruguay.","DOI":"10.1109\/LASCAS.2015.7250438"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1617","DOI":"10.1109\/TNS.2015.2447391","article-title":"A Methodology to Emulate Single Event Upsets in Flip-Flops using FPGAs through Partial Reconfiguration and Instrumentation","volume":"62","author":"Serrano","year":"2015","journal-title":"IEEE Trans. Nucl. Sci."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Hopson, B., Benkrid, K., Keymeulen, D., and Aranki, N. (2012, January 25\u201328). Real-time CCSDS lossless adaptive hyperspectral image compression on parallel GPGPU & multicore processor systems. Proceedings of the 2012 NASA\/ESA Conference on Adaptive Hardware and Systems (AHS), Erlangen, Germany.","DOI":"10.1109\/AHS.2012.6268637"},{"key":"ref_18","unstructured":"(2017, September 19). AVIRIS Website, Available online: https:\/\/aviris.jpl.nasa.gov\/aviris\/instrument.html."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"399","DOI":"10.1109\/TIT.1966.1053907","article-title":"Run-length encodings","volume":"12","author":"Golomb","year":"1966","journal-title":"IEEE Trans. Inf. Theory"},{"key":"ref_20","unstructured":"(2017, September 19). GICI Group, Empord\u00e1 Software, Universitat Autonoma de Barcelona, 2011. Available online: http:\/\/www.gici.uab.es."},{"key":"ref_21","unstructured":"(2017, September 19). Luca Fossati, Lossless Ccsds. European Space Agency, 2011. Available online: https:\/\/amstel.estec.esa.int\/tecedm\/misc\/ESA_OSS_license.html."},{"key":"ref_22","unstructured":"(2017, September 19). Texas Instruments\u2019s USB Interface Adapter EVM. Available online: http:\/\/www.ti.com\/tool\/usb-to-gpio."},{"key":"ref_23","unstructured":"(2017, September 19). Xilinx Power Estimator. Available online: https:\/\/www.xilinx.com\/products\/technology\/power\/xpe.html."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/9\/10\/973\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T18:45:32Z","timestamp":1760208332000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/9\/10\/973"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,9,21]]},"references-count":23,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2017,10]]}},"alternative-id":["rs9100973"],"URL":"https:\/\/doi.org\/10.3390\/rs9100973","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2017,9,21]]}}}