Future high resolution instruments planned by CNES for space remote sensing missions will lead to higher bit rates because of the increase in resolution and dynamic range. For example, the ground resolution improvement induces a data rate multi-plied by 8 from SPOT4 to SPOT5 and by 28 to PLEIADES-HR. Lossy data compression with low complexity algorithms is then needed since compression ratio are always higher. New image compression algorithms have been used to increase their compression performance while complying with image quality requirements from the community of users and experts. Thus, DPCM algorithm used on-board SPOT4 was replaced by a DCT-based compressor on-board SPOT5. Recent compression algorithms such as PLEIADES-HR one use a wavelet-transform and a bit-plane encoder. But future compressors will have to be more powerful to reach higher compression ratios. New transforms are studied by CNES to exceed the DWT but a per-formance gap could be obtained with selective compression. This article gives an overview of CNES past and present studies of on-board compression algorithms for high-resolution images.
CNES has launched in May 2002 a new high resolution (2.5m) and large swath (2 x 60km) optical remote sensing satellite: SPOT5. To achieve a high image acquisition capacity with this system, a large on-board mass memory (100 Gbits) together with a 3:1 real-time compression are being used. The quasi-lossless and fixed output rate requirements put on the on-board image compression resulted in the development of a custom algorithm. This algorithm is based on: a DCT decorrelator, a scalar quantizer, an entropy coder and a rate regulator. It has been extensively tested before launch both in terms of quantitative performances and in terms of visual performances. The objectives of the on-orbit validation of the SPOT5 image compression function were the following: (1) Perform an image quality assessment in worst case conditions for the compression. In particular, the THR mode (2.5 m resolution) is potentially sensitive to compression noise and was therefore thoroughly checked for any compression artefacts. Compression noise characteristics were taken into account in the denoising stage of the ground processing for improved performances; (2) Verify the adequacy of the compression parameters with regard to the in-flight characteristics of the instruments (MTF, radiometric spreading, ...); (3) Technological checkout of the compression unit on board the satellite.
This paper will present an overview of SPOT5 mission, the methods used for on-orbit validation of the compression and, finally, all the validation results together with the lessons learned throughout this development. On-board image compression for future CNES remote sensing missions will be addressed as a conclusion.
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.
The Consultative Committee for Space Data Systems (CCSDS) has been engaging in recommending data compression standards for space applications. The first effort focused on a lossless scheme that was adopted in 1997. Since then, space missions benefiting from this recommendation range from deep space probes to near Earth observatories. The cost savings result not only from reduced onboard storage and reduced bandwidth, but also in ground archive of mission data. In many instances, this recommendation also enables more science data to be collected for added scientific value. Since 1998, the compression sub-panel of CCSDS has been investigating lossy image compression schemes and is currently working towards a common solution for a single recommendation. The recommendation will fulfill the requirements for remote sensing conducted on space platforms.
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.
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.
Improving the ground resolution of SPOT 5 compared with SPOT 4 involves multiplying the data rate by 4. This made it necessary to seek a new image compression algorithm able to significantly increase the compression ratio while complying with the image quality requirements of SPOT users. We finally selected a DCT based algorithm embedded in a regulation loop in order to obtain a constant rate at the compressor output. This algorithm was first tested using simulated images. Quantitative and qualitative analyses were carried out at different development stages. Finally, a wide range of images chosen from the SPOT image database was used for validation purpose. This led us to propose several optimizations which have now been thoroughly tested. The result is an almost lossless compression algorithm, which will be used on both SPOT5 and HELIOS II, the French space agency's forthcoming Earth observation missions.