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Fixed-quality/variable bit-rate on-board image compression for future CNES missions

机译:固定质量/可变比特率车载图像压缩,可用于未来的CNES任务

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The huge improvements in resolution and dynamic range of current [1][2] and future CNES remote sensing missions(from 5m/2.5m in Spot5 to 70cm in Pleiades) illustrate the increasing need of efficient on-board image compressors.Many techniques have been considered by CNES during the last years in order to go beyond usual compression ratios:new image transforms or post-transforms [3][4], exceptional processing [5], selective compression [6].However, even if significant improvements have been obtained, none of those techniques has ever contested an essentialdrawback in current on-board compression schemes: fixed-rate (or compression ratio).This classical assumption provides highly-predictable data volumes that simplify storage and transmission. But on theother hand, it demands to compress every image-segment (strip) of the scene within the same amount of data. Therefore,this fixed bit-rate is dimensioned on the worst case assessments to guarantee the quality requirements in all areas of theimage. This is obviously not the most economical way of achieving the required image quality for every single segment.Thus, CNES has started a study to re-use existing compressors [7] in a Fixed-Quality/Variable bit-rate mode. The mainidea is to compute a local complexity metric in order to assign the optimum bit-rate to comply with quality requirements.Consequently, complex areas are less compressed than simple ones, offering a better image quality for an equivalentglobal bit-rate.“Near-lossless bit-rate” of image segments has revealed as an efficient image complexity estimator. It links qualitycriteria and bit-rates through a single theoretical relationship. Compression parameters are thus automatically computedin accordance with the quality requirements. In addition, this complexity estimator could be implemented in a one-passcompression and truncation scheme.© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
机译:当前[1] [2]和未来的CNES遥感任务的分辨率和动态范围的巨大改进(从Spot5中的5m / 2.5m到Pleiades中的70cm)说明了对高效机载图像压缩器的日益增长的需求。在过去的几年中,CNES已考虑将其用于超出通常的压缩率:新图像变换或后变换[3] [4],出色的处理[5],选择性压缩[6]。获得这些数据后,这些技术都无法与目前的车载压缩方案相提并论:固定速率(或压缩率)。这种经典的假设提供了高度可预测的数据量,可以简化存储和传输。但是另一方面,它要求在相同数量的数据内压缩场景的每个图像段(条带)。因此,在最坏情况下评估此固定比特率的大小,以确保图像所有区域的质量要求。显然,这不是实现每个片段所需图像质量的最经济的方法。因此,CNES已开始研究以固定质量/可变比特率模式重用现有的压缩器[7]。主要思想是计算局部复杂度指标,以便分配最佳比特率以符合质量要求。因此,复杂区域的压缩率要比简单区域少,从而在等效的全局比特率下提供更好的图像质量。图像段的“无损比特率”已被证明是一种有效的图像复杂度估计器。它通过单个理论关系将质量标准和比特率联系在一起。因此,根据质量要求自动计算压缩参数。此外,这种复杂性估算器可以采用一次通过压缩和截断的方案来实现。©(2012)COPYRIGHT,美国光电仪器工程师学会(SPIE)。摘要的下载仅允许个人使用。

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