Most images today are processed with AI/ML, where differences in pixel values are critical and may be invisible to the human eye. ML model reliability depends on high-quality data, best achieved with raw images.
Raw data’s size is a bottleneck for transmission speed, processing, storage and associated costs.
Image compression could tackle these, but, currently impose limitations:
Jetraw Core is in-camera raw compression combining the size of lossy formats with the reliability and quality of lossless technologies.
It applies lossless compression to the signal component, following image preparation with lossy compression of the noise. This achieves the highest ratio and the highest quality output on the market.
Jetraw turns data into measurement by embedding a custom noise model
based on the sensor’s physical properties. This enables image quality validation and optimization for AI/ML.