Using GPU-Accelerated Pixel Format Conversions for Efficient Real-Time Video Streaming

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Publisher: SMPTE
Doc Type: Journal Article
Content Type: Original Research
Abbreviated Title: SMPTE Motion Imaging Jour.
Volume: 133, No. 5, pp. 60–70
Abstract: Pixelweave Chromascale is a new open-source library that can leverage GPU computing to efficiently convert video frame pixel formats. The library enhances the computational performance of high-quality real-time video streaming by accelerating pre-frame conversions and offloading resource-intensive tasks from the CPU. It currently supports a wide range of pixel formats, including RGBA and chroma-subsampled YUV, using up to 16 bits per color channel. It is accessed through a C++ interface that triggers a GPU compute pipeline. It uses a novel approach that samples $2 \times 2$ pixel windows, ensuring the code is easily extensible and independent of source and destination formats. Evaluations of multiple video samples demonstrate significant improvement in frames-per-second when compared to existing state-of-the-art CPU-based libraries and show improved video quality in real-time streaming applications. Pixelweave technology has been integrated into a production tool to create numerous award-winning films, enabling more performant and color-accurate real-time streaming.
Publication Date: 2024-09-01
DOI: 10.5594/JMI.2024/YPJG9446
ISSN: Print: 1545-0279 | Electronic: 2160-2492
Link: https://doi.org/10.5594/JMI.2024/YPJG9446
Author(s): Jose Aguerre
Bruno Sena
Damien Stolarz
Keyword(s): Real-Time Video, GPU Computing, Pixel Formats
Copyright: © 2024 SMPTE

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Jose Aguerre, Bruno Sena, and Damien Stolarz; Using GPU-Accelerated Pixel Format Conversions for Efficient Real-Time Video Streaming, MIJ 2024, Volume 133, Number 5 (pp. 60 to 70); SMPTE, 2024. Available at https://doi.org/10.5594/JMI.2024/YPJG9446

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Jose Aguerre, Bruno Sena, and Damien Stolarz; Using GPU-Accelerated Pixel Format Conversions for Efficient Real-Time Video Streaming, MIJ 2024, Volume 133, Number 5 (pp. 60 to 70); SMPTE, 2024. Available at https://doi.org/10.5594/JMI.2024/YPJG9446

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<span class="citation">Jose Aguerre, Bruno Sena, and Damien Stolarz; <cite>Using GPU-Accelerated Pixel Format Conversions for Efficient Real-Time Video Streaming</cite>, MIJ 2024, Volume 133, Number 5 (pp. 60 to 70); SMPTE, 2024. Available at <a href="https://doi.org/10.5594/JMI.2024/YPJG9446" target="_blank" rel="noopener">https://doi.org/10.5594/JMI.2024/YPJG9446</a></span>

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Jose Aguerre, Bruno Sena, and Damien Stolarz; Using GPU-Accelerated Pixel Format Conversions for Efficient Real-Time Video Streaming, MIJ 2024, Volume 133, Number 5 (pp. 60 to 70); SMPTE, 2024
doi: 10.5594/JMI.2024/YPJG9446
url: https://doi.org/10.5594/JMI.2024/YPJG9446

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<li>
Jose Aguerre, Bruno Sena, and Damien Stolarz; <cite id="bib-10-5594-jmi-2024-ypjg9446">Using GPU-Accelerated Pixel Format Conversions for Efficient Real-Time Video Streaming</cite>, MIJ 2024, Volume 133, Number 5 (pp. 60 to 70); SMPTE, 2024
<span class="doi">10.5594/JMI.2024/YPJG9446</span>
</li>