Efficient Satellite Imagery Compression System: Earth+

Grunnleggende konsepter

Earth+ introduces a novel approach to satellite imagery compression, leveraging constellation-wide sharing of fresh reference images to reduce downlink usage significantly.

Sammendrag

Earth observation satellites face downlink limitations, hindering data availability. Earth+ addresses this by utilizing fresh reference images from multiple satellites in a constellation, reducing downlink bandwidth by 1.3-3.3x without compromising image quality. By selecting cloud-free references and compressing changed tiles efficiently, Earth+ optimizes onboard storage and uplink bandwidth usage.

Statistikk

Earth+ reduces downlink usage by a factor of 3.3 compared to state-of-the-art techniques.
Uplink bandwidth: 250 kbps in DOVEs constellation.

Sitater

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Earth+

by Kuntai Du,Yi... klokken arxiv.org 03-19-2024

https://arxiv.org/pdf/2403.11434.pdf

Dypere Spørsmål

How does Earth+ handle fluctuating uplink and downlink bandwidth?

Earth+ handles fluctuating uplink bandwidth by locally caching reference images onboard the satellite. When the capacity of the uplink changes, Earth+ can skip updating some reference images and rely on old cached references for change detection. This allows Earth+ to adapt to variations in uplink bandwidth without compromising performance. For fluctuations in downlink bandwidth, Earth+ relies on a layered codec that enables smooth trade-offs between downlink usage and image quality. By encoding images into multiple layers, Earth+ can adjust the amount of data downloaded based on available bandwidth.

What are the implications of using low-resolution reference images for compression efficiency?

Using low-resolution reference images has several implications for compression efficiency in Earth+. Downsampling reference images helps reduce storage requirements onboard satellites and speeds up processing by detecting changes at a lower resolution. While downsampling may lead to less accurate change detection compared to full-resolution references, it minimizes false negatives by setting appropriate thresholds for detecting changed tiles. Additionally, compressing low-resolution references allows Earth+ to efficiently pinpoint only the changed areas for download, resulting in significant savings in downlink usage without sacrificing image quality.

How can Earth+'s approach be applied to other data-intensive industries beyond satellite imagery?

Earth+'s approach of leveraging historical data and constellation-wide sharing of fresh reference images can be applied to various data-intensive industries beyond satellite imagery. For example:

Healthcare: Medical imaging systems could benefit from similar techniques by comparing current scans with historical patient records or population datasets.
Smart Cities: Urban planning applications could use constellation-wide sharing of real-time sensor data across different city infrastructure components.
Environmental Monitoring: Climate monitoring systems could utilize shared historical observations from global networks of sensors or satellites.
Financial Services: Fraud detection systems could leverage past transaction patterns across multiple financial institutions within a network.
By adapting Earth+'s methodology to these industries, organizations can optimize data transmission efficiency while maintaining high-quality insights derived from large datasets across distributed networks or platforms.