发表机构
Coovally; Technical University of Vienna; Peking University; Beijing University of Posts and Telecommunications; ICREA（库瓦利公司; 维也纳技术大学; 北京大学; 北京邮电大学; 加泰罗尼亚研究与高级研究所）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究针对卫星下行链路图像传输问题，提出清晰加权比特分配方法，训练带清晰概率加权损失的神经编解码器，设计因果调度器，在匹配清晰区域质量时减少字节需求，提升截止日期完整交付量。
AI 中文摘要
地球观测卫星捕获的图像超过了间歇性地面接触可传输的量。星载系统对云检测器进行阈值处理，丢弃帧或图块，并使用固定编解码器压缩剩余内容。在专家标记的图像上，这些规则会清除超过五分之一的清晰像素，主要是由于检测器的误报。我们训练了一种带有清晰概率加权重构损失的神经编解码器，将编码字节从云重新分配到清晰地面，无需在星上要求或传输云图。每次捕获被编码为可恢复的基础层和依赖的细化层，而清晰内容则从编码器产生的特征中估计。在每次接触时，我们使用估计的清晰内容、未完成的字节、截止日期松弛和总截止日期压力对到达的层进行因果排序。调度器满足基础和计算截止日期，限制存储的残差字节，并恢复中断的数据包。我们使用真实的熵编码字节、轨道衍生的可中断接触容量，以及在资源受限的嵌入式加速器上测量的服务时间和能量，评估星载到下行链路的流水线。在匹配清晰区域质量的情况下，清晰加权编解码器比学习压缩基线需要少达47.8%的字节。优化后的编码器比帧丢弃规则使用的云检测器的一次传递消耗更少的时间和能量。相对于相同流上的固定两阶段服务，我们的调度器使中断组合队列的截止日期完整清晰内容交付量增加了一倍以上，达到认证的全知上限的83.6%，并在截止日期可用交付中超过了重放参考顺序。
英文摘要
Earth-observation satellites capture more imagery than intermittent ground contacts can transmit. Onboard systems threshold a cloud detector, discard frames or tiles, and compress the survivors with a fixed codec. On expert-labeled imagery, these rules remove more than one-fifth of clear pixels, primarily through detector false positives. We train a neural codec with a clear-probability-weighted reconstruction loss, reallocating coded bytes from clouds to clear ground without requiring or transmitting a cloud map onboard. Each capture is encoded into a resumable base layer and a dependent refinement layer, while clear content is estimated from features produced by the encoder. At each contact, we causally rank arrived layers using estimated clear content, unfinished bytes, deadline slack, and aggregate deadline pressure. The scheduler serves base and computational deadlines, bounds stored residual bytes, and resumes interrupted packets. We evaluate the onboard-to-downlink pipeline using real entropy-coded bytes, orbit-derived interruptible contact capacities, and measured service time and energy on resource-constrained embedded accelerators. Clear-weighted codecs require up to 47.8\% fewer bytes than learned-compression baselines at matched clear-region quality. The optimized encoder consumes less time and energy than one pass of the cloud detector used by the frame-discard rules. Relative to fixed two-stage service on the same streams, our scheduler more than doubles deadline-full clear-content delivery for the interrupted combined cohort, reaches 83.6\% of a certified clairvoyant upper bound, and exceeds replayed reference orders in deadline-usable delivery.
Comments10 pages, 11 Figures, 6 Tables
