Open-source Encoder Research Articles

Genie: the first open-source ISO/IEC encoder for genomic data

For the last two decades, the amount of genomic data produced by scientific and medical applications has been growing at a rapid pace. To enable software solutions that analyze, process, and transmit these data in an efficient and interoperable way, ISO and IEC released the first version of the compression standard MPEG-G in 2019. However, non-proprietary implementations of the standard are not openly available so far, limiting fair scientific assessment of the standard and, therefore, hindering its broad adoption. In this paper, we present Genie, to the best of our knowledge the first open-source encoder that compresses genomic data according to the MPEG-G standard. We demonstrate that Genie reaches state-of-the-art compression ratios while offering interoperability with any other standard-compliant decoder independent from its manufacturer. Finally, the ISO/IEC ecosystem ensures the long-term sustainability and decodability of the compressed data through the ISO/IEC-supported reference decoder.

Choosing Encoding Parameters for High-Dynamic Range Streaming

This paper provides data and analysis on the impact of various high-dynamic range (HDR) encoding options on video quality and bitrate. Specifically, this paper examines permutations of perceptual quantizer (PQ), hybrid-log gamma (HLG), <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${Y}^\prime ~C_{B}C_{R}$ </tex-math></inline-formula> , IC <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$_{T}C_{P}$ </tex-math></inline-formula> , encoded resolution, and bitrate using the open-source encoder <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times 265$ </tex-math></inline-formula> . Video distortion for each permutation is measured using publicly available nonproprietary objective video quality metrics. Today, we have two different ways of mapping light to HDR code values: PQ and HLG. We also have the option of representing color and luminance as either <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${Y}^\prime ~C_{B}C_{R}$ </tex-math></inline-formula> or the newer alternative IC <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$_{T}C_{P}$ </tex-math></inline-formula> . For HDR adaptive bitrate streaming, we need to choose which compression levels and encoding resolutions to use when we create adaptation sets; but we do not yet have a complete understanding of how resolution and compression could interact to alter the highlights and deep darks that make HDR so visually potent. When viewed altogether, the many permutations of HDR encoding can make designing an HDR streaming service complicated and uncertain. This paper provides practical data and analysis that can be used to make designing HDR streaming services easier and more predictable. <disp-quote xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> This paper provides practical data and analysis that can be used to make designing HDR streaming services easier and more predictable. </disp-quote>