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.
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.
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.
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.