Capturing global redundancy to improve compression of large images

Barbara L. Kess, Stephen E. Reichenbach

Research output: Contribution to journalConference articlepeer-review


A Source Specific Model for Global Earth Data (SSM-GED) is a lossless compression method for large images that captures global redundancy in the data and achieves a significant improvement over CALIC and DCXT-BT/CARP, two leading lossless compression schemes. The Global Land 1-Km Advanced Very High Resolution Radiometer (AVHRR) data, which contains 662 Megabytes (MB) per band, is an example of a large data set that requires decompression of regions of the data. For this reason, SSM-GED compresses the AVHRR data as a collection of subwindows. This approach defines the statistical parameters for the model prior to compression. Unlike universal models that assume no a priori knowledge of the data, SSM-GED captures global redundancy that exists among all of the subwindows of data. The overlap in parameters among subwindows of data enables SSM-GED to improve the compression rate by increasing the number of parameters and maintaining a small model cost for each subwindow of data.

Original languageEnglish (US)
Pages (from-to)62-71
Number of pages10
JournalData Compression Conference Proceedings
StatePublished - 1997
Externally publishedYes
EventProceedings of the 1997 Data Compression Conference, DCC'97 - Snowbird, UT, USA
Duration: Mar 25 1997Mar 27 1997

ASJC Scopus subject areas

  • Computer Networks and Communications


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