AV1@规模:胶片颗粒合成,觉醒
AV1@Scale: Film Grain Synthesis, The Awakening

原始链接: https://netflixtechblog.com/av1-scale-film-grain-synthesis-the-awakening-ee09cfdff40b

Netflix的陈立恒及其团队正在通过大规模部署AV1胶片颗粒合成技术(FGS)来提升流媒体观看体验。FGS解决了胶片颗粒压缩的难题。胶片颗粒对于视觉深度和真实感至关重要,但传统压缩方法难以有效处理。 FGS通过两个组件对胶片颗粒进行建模:胶片颗粒图案,利用自回归(AR)系数复制颗粒的空间相关性;以及胶片颗粒强度,使用分段线性缩放函数根据光线调整颗粒强度。 编码过程会先对视频进行降噪处理,然后压缩视频,并传输颗粒图案和强度信息。播放时,系统会重新创建并整合颗粒,从而优化播放流畅度。通过在压缩前去除颗粒,视频更容易压缩,从而节省大量比特率,同时保留原始胶片颗粒的艺术完整性,最终提升视觉质量。以《他们克隆了泰隆》为例,FGS提供了优质的流媒体观看体验。

The Hacker News discussion revolves around Netflix's AV1 film grain synthesis (FGS) and its impact on video quality and compression. The technique removes grain before encoding, then re-adds it during playback to save bandwidth. Some argue that synthesized grain lacks the detail of real grain, leading to a blurrier viewing experience, as real grain can subtly encode details. Others point out that denoising can also remove real detail, and FGS at least allows for more bits to be allocated to actual image content. The debate extends to whether grain is inherently desirable, with some finding it aesthetically pleasing and reminiscent of classic film, while others view it as an unnecessary flaw. Many acknowledge that grain can mask compression artifacts and increase perceived sharpness. The discussion touches upon the role of compression artifacts, viewing habits and technology choices and also veers into film's overall look, frame rates, noise, and what should be prioritized. Overall, the sentiment leans towards accepting FGS as a practical compromise for streaming, provided the synthesized grain can be improved to more closely resemble the real thing and the process does not erase original artistic intent.
相关文章

原文
Netflix Technology Blog

Li-Heng Chen, Andrey Norkin, Liwei Guo, Zhi Li, Agata Opalach and Anush Moorthy

Picture this: you’re watching a classic film, and the subtle dance of film grain adds a layer of authenticity and nostalgia to every scene. This grain, formed from tiny particles during the film’s development, is more than just a visual effect. It plays a key role in storytelling by enhancing the film’s depth and contributing to its realism. However, film grain is as elusive as it is beautiful. Its random nature makes it notoriously difficult to compress. Traditional compression algorithms struggle to manage it, often forcing a choice between preserving the grain and reducing file size.

In the digital age, noise remains a ubiquitous element in video content. Camera sensor noise introduces its own characteristics, while filmmakers often add intentional grain during post-production to evoke mood or a vintage feel. These elements create a visually rich experience that tests conventional compression methods.

We’re giving members globally a transformed streaming experience with the recent rollout of AV1 Film Grain Synthesis (FGS) streams. While FGS has been part of the AV1 standard since its inception, we only enabled it for a limited number of titles during our initial launch of the AV1 codec in 2021. Now, we’re enabling this innovative technology at scale, leveraging it to preserve the artistic integrity of film grain while optimizing data efficiency. In this blog post, we’ll explore how FGS revolutionizes video streaming and enhances your viewing experience.

The AV1 Film Grain Synthesis tool models film grain through two key components, with model parameters estimated before the encoding of the denoised video:

Film Grain Pattern: an auto-regressive (AR) model is used to replicate the pattern of film grain. The key parameters are the AR coefficients, which can be estimated from the residual between the source video and the denoised video, essentially capturing the noise. This model captures the spatial correlation between the grain samples, ensuring that the noise characteristics of the original content are accurately preserved. By adjusting the auto-regressive coefficients {ai}, the model can control the grain’s shape, making it appear coarser or finer. With these coefficients, a 64x64 noise template is generated, as illustrated in the animation below. To construct the noise layer during playback, random 32x32 patches are extracted from the 64x64 noise template and added to the decoded video.

Fig. 1 The synthesis process of the 64x64 noise template using the simplest AR kernel with a lag parameter L=1. Each noise value is calculated as a linear combination of previously synthesized noise sample values, with AR coefficients a0, a1, a2, a3 and a white Gaussian noise (wgn) component.

Film Grain Intensity: a scaling function is employed to control the grain’s appearance under varying lighting conditions. This function, estimated during the encoding process, models the relationship between pixel value and noise intensity using a piecewise linear function. This allows for precise adjustments to the grain strength based on video brightness and color. Consequently, the film grain strength is adapted to the areas of the picture, closely recreating the look of the original video. The animation below demonstrates how the grain intensity is adjusted by the scaling function:

Fig. 2 Illustration of the scaling function’s impact on film grain intensity. Left: The scaling function graph showing the relationship between pixel value and scaling intensity. Right: A grayscale SMPTE bars frame with film grain applied according to the scaling function.

With these models specified by AV1 standard, the encoding process first removes the film grain from the video. The standard does not mandate a specific method for this step, allowing users to choose their preferred denoiser. Following the denoising, the video is compressed, and the grain’s pattern and intensity are estimated and transmitted alongside the compressed video data. During playback, the film grain is recreated and reintegrated into the video using a block-based method. This approach is optimized for consumer devices, ensuring smooth playback and high-quality visuals. For a more detailed explanation, please refer to the original paper.

By combining these components, the AV1 Film Grain Synthesis tool preserves the artistic integrity of film grain while making the content “easier to compress” by denoising the source video prior to encoding. This process enables high-quality video streaming, even in content with heavy grain, resulting in significant bitrate savings and improved visual quality.

In our pursuit of premium streaming quality, enabling AV1 Film Grain Synthesis has led to significant bitrate reduction, allowing us to deliver high-quality video with less data while preserving the artistic integrity of film grain. Below, we showcase visual examples highlighting the improved quality and reduced bitrate, using a frame from the Netflix title They Cloned Tyrone:

联系我们 contact @ memedata.com