Unravelling the Power of Single-Pass Look-Ahead in Modern Codecs for Optimized Transcoding Deployment

Modern video encoders have evolved into sophisticated pieces of software in which various coding tools interact with each other. In the past, singlepass encoding was not considered for Video-On-Demand (VOD) use cases. In this work, we evaluate production-ready encoders for H.264 (x264), H.265 (HEVC), AV1 (SVT-AV1) along with direct comparisons to the latest AV1 encoder inside NVIDIA GPUs (40 series), and AWS Mediaconvert's AV1 implementation. Our experimental results demonstrate single pass encoding inside modern encoder implementations can give us very good quality at a reasonable compute cost. The results are presented as three different scenarios targeting High, Medium, and Low complexity accounting quality/bitrate/compute load. Finally, a set of recommendations is presented for end-users to help decide which encoder/preset combination might be more suited to their use case.

Subjective assessment of the impact of a content adaptive optimiser for compressing 4K HDR content with AV1

Since 2015 video dimensionality has expanded to higher spatial and temporal resolutions and a wider colour gamut. This High Dynamic Range (HDR) content has gained traction in the consumer space as it delivers an enhanced quality of experience. At the same time, the complexity of codecs is growing. This has driven the development of tools for content-adaptive optimisation that achieve optimal rate-distortion performance for HDR video at 4K resolution. While improvements of just a few percentage points in BD-Rate (1-5\%) are significant for the streaming media industry, the impact on subjective quality has been less studied especially for HDR/AV1. In this paper, we conduct a subjective quality assessment (42 subjects) of 4K HDR content with a per-clip optimisation strategy. We correlate these subjective scores with existing popular objective metrics used in standard development and show that some perceptual metrics correlate surprisingly well even though they are not tuned for HDR. We find that the DSQCS protocol is too insensitive to categorically compare the methods but the data allows us to make recommendations about the use of experts vs non-experts in HDR studies, and explain the subjective impact of film grain in HDR content under compression.

Recommendations for Verifying HDR Subjective Testing Workflows

Over the past few years, there has been an increase in the demand and availability of High Dynamic Range (HDR) displays and content. To ensure the production of high-quality materials, human evaluation is required. However, ascertaining whether the full playback pipeline is indeed HDR-compliant can be challenging. In this paper, we present a set of recommendations for conformance testing to validate various aspects of the testing workflow, including playback, displays, brightness, colours, and viewing environment. We assessed the effectiveness of HDR conversion techniques used in current standards development (3GPP) for making source materials. Additionally, we evaluate HDR display technologies, including OLED and LCD, using both consumer television and a reference monitor.

Filling the gaps in video transcoder deployment in the cloud

Cloud-based deployment of content production and broadcast workflows has continued to disrupt the industry after the pandemic. The key tools required for unlocking cloud workflows, e.g., transcoding, metadata parsing, and streaming playback, are increasingly commoditized. However, as video traffic continues to increase there is a need to consider tools which offer opportunities for further bitrate/quality gains as well as those which facilitate cloud deployment. In this paper we consider preprocessing, rate/distortion optimisation and cloud cost prediction tools which are only just emerging from the research community. These tools are posed as part of the per-clip optimisation approach to transcoding which has been adopted by large streaming media processing entities but has yet to be made more widely available for the industry.

Comparison of HDR quality metrics in Per-Clip Lagrangian multiplier optimisation with AV1

The complexity of modern codecs along with the increased need of delivering high-quality videos at low bitrates has reinforced the idea of a per-clip tailoring of parameters for optimised rate-distortion performance. While the objective quality metrics used for Standard Dynamic Range (SDR) videos have been well studied, the transitioning of consumer displays to support High Dynamic Range (HDR) videos, poses a new challenge to rate-distortion optimisation. In this paper, we review the popular HDR metrics DeltaE100 (DE100), PSNRL100, wPSNR, and HDR-VQM. We measure the impact of employing these metrics in per-clip direct search optimisation of the rate-distortion Lagrange multiplier in AV1. We report, on 35 HDR videos, average Bjontegaard Delta Rate (BD-Rate) gains of 4.675%, 2.226%, and 7.253% in terms of DE100, PSNRL100, and HDR-VQM. We also show that the inclusion of chroma in the quality metrics has a significant impact on optimisation, which can only be partially addressed by the use of chroma offsets.

Pushing The Limits of the Wiener Filter in Image Denoising

As modern image denoiser networks have grown in size, their reported performance in popular real noise benchmarks such as DND and SIDD have now long outperformed classic non-deep learning denoisers such as Wiener and Wavelet-based methods. In this paper, we propose to revisit the Wiener filter and re-assess its potential performance. We show that carefully considering the implementation of the Wiener filter can yield similar performance to popular networks such as DnCNN.

Frame-type Sensitive RDO Control for Content-Adaptive-encoding

Video transcoding is an increasingly important application in the streaming media industry. It has become important to investigate the optimisation of transcoder parameters for a single clip simply because of the immense number of playbacks for popular clips. In this paper, we explore the use of a canned optimiser to estimate the optimal RD tradeoff achievable for a particular clip. We show that by adjusting the Lagrange multiplier in RD optimisation on keyframes alone we can achieve more than 10$\times$ the previous BD-Rate gains possible without affecting quality for any operating point.

Near Optimal Per-Clip Lagrangian Multiplier Prediction in HEVC

The majority of internet traffic is video content. This drives the demand for video compression to deliver high quality video at low target bitrates. Optimising the parameters of a video codec for a specific video clip (per-clip optimisation) has been shown to yield significant bitrate savings. In previous work we have shown that per-clip optimisation of the Lagrangian multiplier leads to up to 24% BD-Rate improvement. A key component of these algorithms is modeling the R-D characteristic across the appropriate bitrate range. This is computationally heavy as it usually involves repeated video encodes of the high resolution material at different parameter settings. This work focuses on reducing this computational load by deploying a NN operating on lower bandwidth features. Our system achieves BD-Rate improvement in approximately 90% of a large corpus with comparable results to previous work in direct optimisation.

Per-clip adaptive Lagrangian multiplier optimisation with low-resolution proxies

This work focuses on reducing the computational cost of repeated video encodes by using a lower resolution clip as a proxy. Features extracted from the low resolution clip are used to learn an optimal lagrange multiplier for rate control on the original resolution clip. In addition to reducing the computational cost and encode time by using lower resolution clips, we also investigate the use of older, but faster codecs such as H.264 to create proxies. This work shows that the computational load is reduced by 22 times using 144p proxies. Our tests are based on the YouTube UGC dataset, hence our results are based on a practical instance of the adaptive bitrate encoding problem. Further improvements are possible, by optimising the placement and sparsity of operating points required for the rate distortion curves.

Per Clip Lagrangian Multiplier Optimisation for HEVC

The majority of internet traffic is video content. This drives the demand for video compression in order to deliver high quality video at low target bitrates. This paper investigates the impact of adjusting the rate distortion equation on compression performance. An constant of proportionality, k, is used to modify the Lagrange multiplier used in H.265 (HEVC). Direct optimisation methods are deployed to maximise BD-Rate improvement for a particular clip. This leads to up to 21% BD-Rate improvement for an individual clip. Furthermore we use a more realistic corpus of material provided by YouTube. The results show that direct optimisation using BD-rate as the objective function can lead to further gains in bitrate savings that are not available with previous approaches.