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A Tutorial on Image Compression for Optical Space Imaging Systems

delete2014-09-01
delete83
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OA
AI
I
Ian Blanes *
E
Enrico Magli
J
Joan Serra-Sagristà
DOI:10.1109/MGRS.2014.2352465delete
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Abstract

Abstract

En 中文
Public policies and private initiatives share the will to explore outer space and to monitor the Earth from space sensors. Recent years have seen an increased number of space missions, while the sensors on board aircrafts or spacecrafts have also significantly improved their acquisition capabilities. Given this huge volume of remote sensing data and the detailed characteristics of the acquired images, a data compression process is in order to allow as large a transmission rate as possible. In this paper we provide an overview of several standards for remote sensing data compression, notably of those recently approved by the Consultative Committee for Space Data Systems, although the use of other ISO/IEC image coding standards is also dealt with. Discussion embraces both mono band and multi band compression, and lossless, lossy and near-lossless compression. Illustrative results are reported for a set of AVIRIS and Hyperion images, indicating that exploiting the spectral correlation-either in prediction-based or in transform-based schemes-is paramount to achieve improved coding performance.
Keywords:
NEAR-LOSSLESS COMPRESSION
TRANSFORM
ALGORITHM
LOSSY
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Journal

IEEE Geoscience and Remote Sensing Magazine cover
IEEE Geoscience and Remote Sensing Magazine
IF:
16.4
Papers:
1.0W
Citations:
5.1K

Organization

P
Polytechnic University of Turin
Scholars:
1.3W
Papers: 1.3W
Citations: 1.3W
A
Autonomous University of Barcelona
Scholars:
3.7W
Papers: 2.6W
Citations: 47
Cited Papers

Cited Papers

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