Coding Scheme for the Transmission of Satellite Imagery

Francesc Auli-Llinas, Michael W. Marcellin, Victor Sanchez, Joan Serra-Sagrista, Joan Bartrina-Rapesta, Ian Blanes

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations


The coding and transmission of the massive datasets captured by Earth Observation (EO) satellites is a critical issue in current missions. The conventional approach is to use compression on board the satellite to reduce the size of the captured images. This strategy exploits spatial and/or spectral redundancy to achieve compression. Another type of redundancy found in such data is the temporal redundancy between images of the same area that are captured at different instants of time. This type of redundancy is commonly not exploited because the required data and computing power are not available on board the satellite. This paper introduces a coding scheme for EO satellites able to exploit this redundancy. Contrary to traditional approaches, the proposed scheme employs both the downlink and the uplink of the satellite. Its main insight is to compute and code the temporal redundancy on the ground and transmit it to the satellite via the uplink. The satellite then uses this information to compress more efficiently the captured image. Experimental results for Landsat 8 images indicate that the proposed dual link image coding scheme can achieve higher coding performance than traditional systems for both lossless and lossy regimes.

Original languageEnglish (US)
Title of host publicationProceedings - DCC 2016
Subtitle of host publication2016 Data Compression Conference
EditorsMichael W. Marcellin, Ali Bilgin, Joan Serra-Sagrista, James A. Storer
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages10
ISBN (Electronic)9781509018536
StatePublished - Dec 15 2016
Event2016 Data Compression Conference, DCC 2016 - Snowbird, United States
Duration: Mar 29 2016Apr 1 2016

Publication series

NameData Compression Conference Proceedings
ISSN (Print)1068-0314


Other2016 Data Compression Conference, DCC 2016
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Computer Networks and Communications


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