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The integration of advanced video codecs into the streaming pipeline isgrowing in response to the increasing demand for high quality video content.However, the significant computational demand for advanced codecs likeVersatile Video Coding (VVC) poses challenges for service providers, includinglonger encoding time and higher encoding cost. This challenge becomes even morepronounced in streaming, as the same content needs to be encoded at multiplebitrates (also known as representations) to accommodate different networkconditions. To accelerate the encoding process of multiple representations ofthe same content in VVC, we employ the encoding map of a single representation,known as the reference representation, and utilize its partitioning structureto accelerate the encoding of the remaining representations, referred to asdependent representations. To ensure compatibility with parallel processing, wedesignate the lowest bitrate representation as the reference representation.The experimental results indicate a substantial improvement in the encodingtime for the dependent representations, achieving an average reduction of 40%,while maintaining a minimal average quality drop of only 0.43 in VideoMulti-method Assessment Fusion (VMAF). This improvement is observed whenutilizing Versatile Video Encoder (VVenC), an open and optimized VVC encoderimplementation.

Preparing VVC for Streaming: A Fast Multi-Rate Encoding Approach