A Tutorial on image compression for optical space imaging systems

Abstract-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 cap...

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Detalles Bibliográficos
Autores: Blanes Garcia, Ian|||0000-0001-8939-1666, Magli, Enrico|||0000-0002-0901-0251, Serra-Sagristà, Joan|||0000-0003-4729-9292
Tipo de recurso: artículo
Fecha de publicación:2014
País:España
Institución:Universitat Autònoma de Barcelona
Repositorio:Dipòsit Digital de Documents de la UAB
Idioma:inglés
OAI Identifier:oai:ddd.uab.cat:129766
Acceso en línea:https://ddd.uab.cat/record/129766
https://dx.doi.org/urn:doi:10.1109/MGRS.2014.2352465
Access Level:acceso abierto
Palabra clave:Image compression
Multispectral and hyperspectral images
CCSDS
Prediction
Transform coding
DPCM
Rate control
Descripción
Sumario:Abstract-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.