Uplink-Assist Downlink Remote-Sensing Image Compression via Historical Referencing.

The traditional strategy of acquiring satellite images involves transmitting compressed satellite data to ground stations solely via the downlink, without utilizing the uplink. In this article, we propose an enhanced remote-sensing (RS) image compression approach that utilizes uplink assistance to improve compression efficiency. By leveraging the uplink, historical images from ground stations can serve as reference images for on-orbit compression, effectively eliminating spatiotemporal redundancy in RS images. However, due to radiation variations among RS images captured on different dates, pixel-wise referencing as employed in the prior codec paradigm is insufficient. To address this, we propose a novel dual-end referencing downsampling-based coding (RefDBC) framework. At the encoder, relevance embedding (RE) evaluates reconstructability and records information to restore texture details from the reference before downsampling. At the decoder, relevance-based super-resolution (SR) uses the identical reference and recorded relevance information to reconstruct the decoded low-resolution (LR) image. By incorporating relevance referencing, RefDBC effectively mitigates fake texture generation caused by downsampling and compression, achieving significant bitrate savings ranging from 35% to 70% compared to standard, learning-based, and DBC compression baselines in experiments on Spot-5 and Luojia3 images. Code, data, and pretrained models are available online at https://github.com/WHW1233/RefDBC