Identity statement area
Reference TypeConference Proceedings
Last Update2005: administrator
Metadata Last Update2020: administrator
Citation KeyAcevedoRued:2005:ReInCo
TitleReduction of interband correlation for Landsat image compression.
Date9-12 Oct. 2005
Access Date2020, Dec. 04
Number of Files1
Size454 KiB
Context area
Author1 Acevedo, Daniel Germán
2 Ruedin, Ana María Clara
Affiliation1 University of Buenos Aires
EditorRodrigues, Maria Andréia Formico
Frery, Alejandro César
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 18 (SIBGRAPI)
Conference LocationNatal
Book TitleProceedings
PublisherIEEE Computer Society
Publisher CityLos Alamitos
History2008-07-17 14:11:00 :: daniel -> banon ::
2008-08-26 15:17:02 :: banon -> administrator ::
2009-08-13 20:37:49 :: administrator -> banon ::
2010-08-28 20:01:18 :: banon -> administrator ::
2020-02-19 03:19:13 :: administrator -> :: 2005
Content and structure area
Is the master or a copy?is the master
Document Stagecompleted
Content TypeExternal Contribution
Tertiary TypeFull Paper
KeywordsMultispectral satellite image, correlation, wavelet, lossless compression.
AbstractWe present a lossless compressor for multispectral images that exploits interband correlations. Each band is divided into blocks, to which a wavelet transform is applied. The wavelet coefficients are predicted by means of a linear combination of coefficients belonging to the same orientation and spatial location. The prediction errors are then encoded with an entropy - based coder. Our original contributions are i) the inclusion, among the candidates for prediction, of coefficients of the same location from other spectral bands, ii) the calculation of weights tuned to the landscape being processed, iii) a fast block classification and a different band-ordering for each landscape. Our compressor reduces the size of an image to about a fourth of its original size. Our method is equivalent to LOCO-I, on 3 of the images tested it was superior. It is superior to other lossless compressors: WinZip, JPEG2000 and PNG.
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Target Fileacevedod_lsatcompression.pdf
User Groupdaniel
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