Catherine Lambert-Nebout

On board strip-based wavelet image coding for future space remote sensing missions

Spacecraft sensor obtained data has to be stored on-board until an opportunity arises for it to be transmitted to the ground. Compression algorithms used in space were based first on DPCM and then on DCT. Image quality evaluation determined however that for applications using the adaptive DCT, such as for SPOT 5, the maximum acceptable compression ratio was about 3 for high resolution observation and about 15 for scientific missions. Beyond that compression ratio, the occurrence of block effects in uniform areas and the loss of detail related to compression noise is no more acceptable for scientific use. To overcome these limits and to prepare future generations of Earth observation satellites and scientific missions, the authors propose a novel and efficient strip-based satellite image coder adapted for on board processing. The performances of their method are better than JPEG 2000 with a complexity lower than 60 operations per pixel. Furthermore, their method can be implemented for different image samplings. The authors quickly explain the general compression scheme used and the solution for on the fly DWT computation. They present the dynamic bit allocation and the regulation process chosen for rate control. Then, they evaluate the complexity and performances of their method comparatively to JPEG 2000.

A survey of on-board image compression for CNES space missions

Images acquired on board spacecraft represent in most cases very large volumes of data. It is then necessary to store these data and to transmit them to ground. It is essential to reduce to a minimum the on-board storage capacity and the on-board transmission rate. On board image compression is advantageous for two main reasons: 1) the steady performance improvements of compression algorithms, and 2) the availability in recent years, for spaceborne applications, of highly integrated custom circuits (ASIC technology) which makes it possible to implement, in high pixel rate systems, sophisticated real-time compression schemes. The authors focus on lossy compression algorithms used for CNES space missions. Such a typical image coder has three basic components: a transformation, a quantizer and data coding. In lossy compression the reconstructed image contains degradations relative to the original. As a result, much higher compression can be achieved as compared to lossless compression. More compression is obtained at the expense of more distortion. In order to be acceptable, these degradations (image quality) must be compatible with all the potential uses of the images. It is then very important to consider the whole image chain (from the sensor to the on-ground post-processing) to optimize image compression and for each space mission it is necessary to solve the trade-off between image quality versus compression ratio.

On-board optical image compression for future high-resolution remote sensing systems

Future high resolution instruments planned by CNES to succeed SPOT5 will lead to higher bit rates because of the increase in both resolution and number of bits per pixel, not compensated by the reduced swatch. Data compression is then needed, with compression ratio goals higher than the 2.81 SPOT5 value obtained with a JPEG like algorithm. Compression ratio should rise typically to 4 - 6 values, with artifacts remaining unnoticeable: SPOT5 algorithm performances have clearly to be outdone. On another hand, in the framework of optimized and low cost instruments, noise level will increase. Furthermore, the Modulation Transfer Function (MTF) and the sampling grid will be fitted together, to -- at least roughly -- satisfy Shannon requirements. As with the Supermode sampling scheme of the SPOT5 Panchromatic band, the images will have to be restored (deconvolution and denoising) and that renders the compression impact assessment much more complex. This paper is a synthesis of numerous studies evaluating several data compression algorithms, some of them supposing that the adaptation between sampling grid and MTF is obtained by the quincunx Supermode scheme. The following points are analyzed: compression decorrelator (DCT, LOT, wavelet, lifting), comparison with JPEG2000 for images acquired on a square grid, compression fitting to the quincunx sampling and on board restoration (before compression) versus on ground restoration. For each of them, we describe the proposed solutions, underlining the associated complexity and comparing them from a quantitative and qualitative point of view, giving the results of experts analyses.

Status of onboard image compression for CNES space missions

On board Image compression is a very powerful tool to optimize the onboard resources needed to store and transmit image data to ground. This is due to the steady performance improvements of the compression algorithms and to the availability, for spaceborne applications, of highly integrated circuits (ASIC technology) that made it possible to implement very sophisticated real-time schemes. We propose in this paper a survey of on on-board image compression with emphasis on some compression architectures and present the future prospects.

Fixed-data-rate wavelet compressor for multispectral satellite systems

Future high resolution instruments planned by CNES for space remote sensing missions will lead to higher bit rates because of the increase in both resolution and number of bits per pixel, not compensated by the reduced swath. Data compression is then needed, with compression ratio goals always higher and with artifacts remaining unnoticeable. Up to now studied algorithms are based on intra-band coding and utilize the intra-image or spatial correlation. The spaceborne earth observation instruments have however several spectral channels (one panchromatic band and at least 3 spectral bands) and since such algorithms process independently each channel, the inter-image or spectral correlation is ignored. For optimum compression performance, multispectral algorithms have to be studied in order to exploit both spectral and spatial correlation. This paper proposes a low complexity and flexible fixed data rate compression algorithm for multispectral imagery.

La compression d’images embarquée pour les missions spatiales

RésuméLa quantité de données générées à bord des véhicules spatiaux est de plus en plus importante du fait de l’amélioration constante de la résolution des instruments d’observation optique et du maintien d’une fauchée importante. Malheureusement, les capacités de stockage à bord et de transmission vers le sol sont limitées : il s’avère donc indispensable d’introduire un traitement de compression à bord.Les progrès des technologies électroniques et informatiques embarquées permettent d’intégrer des algorithmes complexes dans les équipements de traitement à bord des satellites et ainsi d’améliorer les performances de la compression embarquée.Les taux de compression doivent cependant rester compatibles des exigences de qualité s’appliquant aux images délivrées par l’ensemble du système qui inclut notamment des traitements au sol sophistiqués (réechantillonnage, déconvolution, débruitage, fusion panchromatique/multispectral) dont l’interaction avec la compression est complexe.Nous décrivons dans cet article les différents algorithmes de compression, utilisés ou en cours d’étude pour des missions spatiales ainsi que les méthodes d’évaluation mises en œuvre et les résultats obtenus.AbstractOn-board space instruments produce more and more high amount of data due to the increase in both resolution and number of bits per pixel, not compensated by the reduced swath. Due to the stringent limitations (in terms of mass and power) which apply to on-board equipment, it is essential to reduce to a minimum the on-board sto-rage capacity and the on-board transmission rate needed to fullfill the mission: on-board image compression is a very powerful tool to optimise the resources.The availability, for spaceborne applications, of highly integrated circuits allows to implement on board very sophisticated real-time compression schemes and then to improve the performances of on-board compression.The whole image chain (from the sensor to the on-ground post-processing such as déconvolution and denoising) has to be considered in order to select the compression algorithm and the compression ratio.This article presents the compression algorithms, selected or currently studied, for space missions, and the methods of image quality evaluation.