{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:32:26Z","timestamp":1760243546085,"version":"build-2065373602"},"reference-count":23,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2012,2,20]],"date-time":"2012-02-20T00:00:00Z","timestamp":1329696000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>Air-borne and space-borne acquired hyperspectral images are used to recognize objects and to classify materials on the surface of the earth. The state of the art compressor for lossless compression of hyperspectral images is the Spectral oriented Least SQuares (SLSQ) compressor (see [1\u20137]). In this paper we discuss hyperspectral image compression: we show how to visualize each band of a hyperspectral image and how this visualization suggests that an appropriate band ordering can lead to improvements in the compression process. In particular, we consider two important distance measures for band ordering: Pearson\u2019s Correlation and Bhattacharyya distance, and report on experimental results achieved by a Java-based implementation of SLSQ.<\/jats:p>","DOI":"10.3390\/a5010076","type":"journal-article","created":{"date-parts":[[2012,2,20]],"date-time":"2012-02-20T11:37:40Z","timestamp":1329737860000},"page":"76-97","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Visualization, Band Ordering and Compression of Hyperspectral Images"],"prefix":"10.3390","volume":"5","author":[{"given":"Raffaele","family":"Pizzolante","sequence":"first","affiliation":[{"name":"Dipartimento di Informatica, Universit\u00e0 di Salerno, Fisciano (SA) 84084, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bruno","family":"Carpentieri","sequence":"additional","affiliation":[{"name":"Dipartimento di Informatica, Universit\u00e0 di Salerno, Fisciano (SA) 84084, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2012,2,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1109\/LSP.2004.840907","article-title":"Low-complexity lossless compression of hyperspectral imagery via linear prediction","volume":"12","author":"Rizzo","year":"2005","journal-title":"IEEE Signal Process. Lett."},{"key":"ref_2","unstructured":"Rizzo, F., Carpentieri, B., Motta, G., and Storer, J.A. (2007). e-Business and Telecommunication Networks, Springer."},{"key":"ref_3","unstructured":"Rizzo, F., Carpentieri, B., Motta, G., and Storer, J.A. (2004, January 23-24). High Performance Compression of Hyperspectral Imagery with Reduced Search Complexity in the Compressed Domain. Proceedings of IEEE Data Compression Conference (DCC \u201904), Snowbird, UT, USA."},{"key":"ref_4","unstructured":"Carpentieri, B., Storer, J.A., Motta, G., and Rizzo, F. (2003, January 25-27). Compression of Hyperspectral Imagery. Proceedings of IEEE Data Compression Conference (DCC \u201903), Snowbird, UT, USA."},{"key":"ref_5","first-page":"182","article-title":"Real-time software compression and classification of hyperspectral images","volume":"5573","author":"Motta","year":"2004","journal-title":"Proceedings of the International Society for Optics and Photonics"},{"key":"ref_6","first-page":"262","article-title":"Lossless compression of hyperspectral imagery: A real-time approach","volume":"5573","author":"Rizzo","year":"2004","journal-title":"Proceedings of the International Society for Optics and Photonics"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Pizzolante, R. (2011, January 21-24). Lossless Compression of Hyperspectral Imagery. 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Image Process."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"S\u00e1nchez, J.E., Auge, E., Santal\u00f3, J., Blanes, I., Serra-Sagrist\u00e0, J., and Kiely, A.B. (2011, January 21-24). Review and Implementation of the Emerging CCSDS Recommended Standard for Multispectral and Hyperspectral Lossless Image Coding. Proceedings of 2011 First International Conference on Data Compression, Communications and Processing (CCP), Palinuro, Italy.","DOI":"10.1109\/CCP.2011.17"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Aul\u00ed Llin\u00e0s, F., Bartrina-Rapesta, J., Serra-Sagrist\u00e0, J., and Marcellin, M.W. (2011, January 21-24). Low Complexity, High Efficiency Probability Model for Hyper-spectral Image Coding. 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Soc."}],"container-title":["Algorithms"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-4893\/5\/1\/76\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:48:58Z","timestamp":1760219338000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-4893\/5\/1\/76"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012,2,20]]},"references-count":23,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2012,3]]}},"alternative-id":["a5010076"],"URL":"https:\/\/doi.org\/10.3390\/a5010076","relation":{},"ISSN":["1999-4893"],"issn-type":[{"type":"electronic","value":"1999-4893"}],"subject":[],"published":{"date-parts":[[2012,2,20]]}}}