Paper
28 December 2000 On-board optical image compression for future high-resolution remote sensing systems
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Abstract
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.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Catherine Lambert-Nebout, Christophe Latry, Gilles A. Moury, Christophe Parisot, Marc Antonini, and Michel Barlaud "On-board optical image compression for future high-resolution remote sensing systems", Proc. SPIE 4115, Applications of Digital Image Processing XXIII, (28 December 2000); https://doi.org/10.1117/12.411557
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CITATIONS
Cited by 14 scholarly publications.
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KEYWORDS
Image compression

Discrete wavelet transforms

Image quality

Modulation transfer functions

Deconvolution

Image filtering

Quantization

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