Image signal processor makes cars see

April 25, 2017 // By Christoph Hammerschmidt
Image signal processor makes cars see
With an Image Signal Processor (ISP) custom-made for automotive applications, ARM takes on the booming market of machine vision for automated vehicles.

Autonomous driving requires more sensors per vehicle – many more than today. While radar and lidar continue to play an important role in the multi-sensor setup enabling the vehicles to create a virtual image of the surroundings, optical cameras will be of paramount importance. Experts expect that future vehicles will contain up to twelve cameras. Even non-autonomous cars will be equipped with cameras: They will replace rear-view mirrors and enable suppliers to enhance their real-world image with digital data. However, even modern cameras and their associated downstream processing chain today are unfit for automotive use, says Richard York, Senior director, Embedded Systems for microprocessor IP vendor ARM. The reasons: Their dynamic range is not even on par with the human eye. Image recognition applications capable of replacing human drivers however need to be at least as good as the human eye, in particular with regards to its adaptability to changing brightness – humans can see in the bright desert sun and in starlight. Not even High Dynamic Range (HDR) cameras today can master this extreme difference between dark and bright. What’s more, the eyes for the robot cars have to offer a similarly high resolution as a human eye, and they have to be fail-safe, they need to meet the requirements of functional safety as described in ISO 26262.


This is where ARM steps in with its latest announcement: ARM’s new MALI-C71 Image Signal Processor (ISP). The MALI-C71 is ARMs first member of a future product family dedicated to address the growing market for automotive cameras, a market with an average growth of 20% annually.

Ultra-wide dynamic range, very high input bandwidth and
 ISO 26262 safety design are the features that make
the MALI C-71 fit for use in autonomous vehicles

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