Improve Earth Observation raw imaging & accelerate data downlink

Power-efficient raw image compression for satellite manufacturers, optical mission operators and satellite image data users.

Reduce data costs

Increase raw image data throughput

Maximise storage capabilities

Improve your AI accuracy

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1.3GB

original raw dataset

0.3GB

compressed raw dataset

Compression ratio

Typically 6:1

Compression speed

FPGA

6.4 Gpx/s

with 32-pixel parallel

Software

6.2 GB/s

(Intel i9 14900k)

Data quality

No artefacts

No bias

No filtering

Large image data in the way of satellite data analysis

Problem

In aerospace, onboard image sensors generate extensive data volumes, resulting in slow data transmission, high energy consumption, and costly infrastructure. Optimizing raw image data workflows for satellite imagery is crucial for advancing Earth Observation and maximizing AI/ML potential.

Existing solutions don't fit AI/ML

Conventional lossless compression is slow and provides a limited compression ratio, failing to address scalability concerns. Meanwhile, visually lossless algorithms jeopardize the robustness of ML models in the context of AI-driven analysis of Earth Observation image data, especially in applications like environmental monitoring, geospatial analysis, and aerial agriculture data.

workflow issues

Jetraw Core — Unlock the true power of satellite images

WHAT IS iT

Jetraw Core stands as a high-efficiency raw image compression solution. It seamlessly integrates into FPGA IP Core or functions as software within data centers. This integration significantly enhances the transmission speed of raw image data while preserving the utmost data quality, thereby ensuring scalable and dependable AI analysis.

BATTLING THE CHALLENGE

Jetraw Core addresses the challenges associated with every step of the aerospace image workflow. It excels in energy efficiency and infrastructure optimization, leading to substantial advantages for both satellite manufacturers and Earth observation data users.

Two implementation routes

Integrate as FPGA IP Core in the system to increase data processing speed & reduce compute requirements

Integrate as a software library to maximise your IT infrastructure and save on storage and increase transfer speed

JETRAW IN A NUTSHELL

High speed

High ratio

Raw quality

No artifacts

Tailored for AI

Enable scalable raw image data management for robust AI processing of EO data

Faster acquisition & I/O

Acquire and transmit raw satellite image data faster between memory, FPGA, CPU, onboard, remote and cloud storage, using existing cable and network

Higher throughput

Achieve a higher raw image data throughput rate (measured in FPS, MB/s, and Mpx/s) with low latency, while conserving computational and bandwidth resources.

Lower energy consumption

Reduce CO₂ emissions related to image data by using smaller storage volumes, efficient logistics, and lower power consumption from payload to ground stations and data centers.

Lower costs & optimised infrastructure

Maximize image downloads within a single downlink, enabling quicker, more cost-effective, and environmentally friendly distribution and storage of Earth Observation image data on the ground.

Accurate data for reliable AI

Jetraw provides format-agnostic raw image quality output. The quality of image data directly impacts the accuracy of ML models and AI-based results of Earth Observationdata.