MIPI Alliance Expands Popular CSI-2 Camera Specification Beyond Mobile
The MIPI Alliance, an international organization that develops interface specifications for mobile and mobile-influenced industries, released MIPI CSI-2 v2.0, a next-generation advancement of its widely used MIPI Camera Serial Interface (CSI-2) specification.
The release expands the applicability of MIPI CSI-2—the global industry’s de facto solution enabling advanced photography and video streaming in mobile devices—to open up more opportunities for innovation on the popular architecture. Designers will be able to innovate, provide even more differentiated features and extend their product lines with v2.0 to target complex imaging and vision needs for mobile, the Internet of Things (IoT), wearables, medical, augmented and virtual reality, drones and automotive systems.
“The MIPI Alliance camera interface architecture is both mature and evolutionary, advancing every two years to anticipate embedded camera and imaging trends and broaden its applicability into new markets,” said Joel Huloux, chairman of the board of MIPI Alliance.
CSI-2 v2.0 can be implemented on either of two physical layers from MIPI Alliance: MIPI C-PHY and MIPI D-PHY. Both physical layer specifications have been updated to support the new CSI-2 v2.0, allowing designers to take full advantage of the latest enhancements while supporting backwards compatibility. This will allow for easy migration to the latest version of MIPI CSI-2 while enabling companies to leverage all investments from previous designs, minimizing development costs and accelerate time to market for new designs.
Key MIPI CSI-2 v2.0 enhancements:
RAW-16 and RAW-20 color depth that vastly improves intra-scene High Dynamic Range (HDR) and Signal to Noise Ratio (SNR) to bring “advanced vision” capabilities to autonomous vehicles and systems
Expanded virtual channels from 4 to 32 to accommodate the proliferation of image sensors with multiple data types and support multi-exposure and multi-range sensor fusion for Advanced Driver Assistance Systems (ADAS) applications such as enhanced collision avoidance
Latency Reduction and Transport Efficiency (LRTE) provides increased image sensor aggregation without adding to system cost; facilitates real-time perception, processing and decision-making; and optimizes transport to reduce the number of wires, toggle rate and power consumption
Differential Pulse Code Modulation (DPCM) 12-10-12 compression, which reduces bandwidth while delivering superior SNR images devoid of compression artifacts for mission-critical vision applications
Scrambling to reduce Power Spectral Density (PSD) emissions, minimize radio interference and allow further reach for longer channels