With the race towards L4+ vehicles, increased number of sensors per car, resolutions, frame rates, etc., the data produced by the systems grows exponentially. So are the costs.
Thus, efficient and cost-effective data handling becomes crucial. Existing infrastructure cannot cope with the demand.
Traditional lossless compression struggles with scalability due to limited speed and efficiency. While visually lossless algorithms compromise the reliability of ML models for the safety of connected and autonomous vehicle’s (CAV).
Jetraw Core is a high-efficiency low-latency 6:1 raw image compression integrated into certified environments, either on-board a vehicle system or in a data centre.
Jetraw applies lossless compression to the signal and lossy compression to the noise, preserving the metrological properties of raw images while achieving higher compression ratios and speeds than traditional lossless methods.
Unlike visually lossless codecs, Jetraw preserves raw quality and treats images as precise measurements, facilitating reliable data-centric AI analysis and model training.
Level 4–5 autonomous vehicles generate massive volumes of image data, often hindered by slow upload and download speeds and recurring system capacity constraints. Cloud storage and access costs can easily reach millions.
Jetraw Core overcomes these challenges and enables scalable data infrastructure for OEMs and Tier 1 suppliers.
