SMPTE ST 2067-70 simplifies VC-3 usage in Interoperable Master Format

The Society of Motion Picture and Television Engineers (SMPTE) and Avid have jointly published a new standard for the VC-3 codec in Interoperable Master Format (IMF).

The VC-3 standard, a codec implementation that Avid provides under the DNx brand, is a primary production codec used by enterprise media organisations around the world for critical broadcast functions such as capture, editing, rendering, base transcoding, and long-term archive. 

SMPTE ST 2067-70 is a new standard that specifies an application of the IMF framework covering usage of VC-3 as specified in SMPTE ST 2019-1.

Shailendra Mathur, VP of Technology, Avid, said, “For many of Avid’s customers, the DNx family of codecs, VC-3, is used in their productions as a mezzanine format to maximise quality while obtaining superior editing performance on common off-the-shelf desktop and server platforms. 

“This newly published standard will ensure that the same mezzanine-quality codec used in production can now be passed through to the IMF mastering stage for distribution.”

MF is a family of SMPTE Standards (SMPTE ST 2067) that simplifies the storage of all the audio-visual content needed to create different versions for distribution to multiple territories and platforms in one package.

It is an essential component of modern, high-scale content fulfilment and has enabled the building of simplified delivery and processing systems for versioning.

As VC-3 is a primary production codec used when delivering to a variety of broadcasters, the new ST 2067-70 standard covers its usage with IMF, which enables delivery in VC-3 codecs that closely matches the ideals of IMF in keeping the maximum quality possible for future distribution/reversion and archive. 

The standard allows any broadcast facility to deliver final assets for broadcast/archive with as much of the original creative intent in place as possible. It also offers a choice to use a constant bit rate (CBR) codec profile, which enables predictability for storage and network transport.