Arm Introduces New Image Signal Processor to Advance Vision Systems for IoT and Embedded Markets
June 13, 2022
News
With increased demand for more and higher quality image processing in future devices, Arm’s ISP technology, the Mali-C55 ISP, is the smallest and most configurable ISP from Arm to date and has its first public licensee, Renesas.
The Mali-C55 delivers upgraded image quality features, works under a wide range of different lighting and weather conditions, and is designed to enable maximum performance and capability in area and power constrained applications, making it ideal for smart camera and edge AI vision use cases.
This advanced technology is designed to deliver improved capabilities in several markets – surveillance and security cameras will be able to detect more critical detail, such as recognizing the exact information on license plates traveling at up to 75mph; home cameras and security systems will capture higher resolution images both inside and out; and smart home hubs can efficiently include advanced features like secure visual unlock.
With multi-camera capability for up to 8 separate inputs, support for image resolutions up to 8K, and a maximum image size up to 48 megapixels (MP), the Mali-C55 offers an efficient combination of image quality, throughput, power consumption, and silicon area. Building on the Mali-C52 ISP, it enables image quality through features including improved tone mapping and spatial noise reduction, enhanced support for high dynamic range (HDR) sensors, and seamless integration with machine learning accelerators to take advantage of neural networks for various de-noising techniques. By combining multiple Mali-C55 ISPs, larger image sizes can be achieved for applications that require greater than 48 MP capabilities, such as video conferencing.
For embedded and IoT vision applications, silicon footprint and cost are important factors, and with the Mali-C55 we’ve provided these enhanced features in almost half of the silicon area size of previous generations, lowering power consumption for extended battery life, and in the process also lowering the cost of these devices.
By enabling easy integration between Mali-C55 and machine learning accelerators, Arm is delivering new levels of on-device processing in devices that require high quality vision systems because the output from the ISP can be sent directly to the ML accelerator. This is designed to reduce cost and processing time by having less data sent from device to cloud, without having to compromise on inferencing.
For developers, Arm is providing a complete software package for controlling the ISP, as well as a full set of tuning and calibration tools to help partners achieve the desired image quality for their application. Additionally, Arm's latest roadmap of Total Solutions for IoT includes an upcoming Total Solution for vision, which will integrate the Mali-C55.
Silicon partners and OEMs need the freedom to easily add or remove features in line with their application requirements, and that’s why Arm designed the Mali-C55 to be their most configurable ISP. In addition to the multi-camera support and integration with ML accelerators already mentioned, the Mali-C55 also includes industry standard AXI and AHB interfaces for easy integration with either Cortex-A or Cortex-M-based SoCs.
For more information, visit: https://developer.arm.com/Processors/Mali-C55
Tiera Oliver is the assistant managing editor at Embedded Computing Design. She is responsible for web content editing, product news, and story development. She also manages, edits, and develops content for ECD podcasts, including Embedded Insiders.
She utilizes her expertise in journalism and content management to oversee editorial content, coordinate with editors, and ensure high-quality output across web, print, and multimedia platforms. She manages diverse projects, assists in the production of digital magazines, and hosts company podcasts by conducting in-depth interviews with industry leaders to deliver engaging and insightful discussions.
Tiera attended Northern Arizona University, where she received her bachelor's in journalism and political science. She was also a news reporter for the student-led newspaper, The Lumberjack.
