HDR has long being heralded as a highly compelling and effective technology as high dynamic range can improve video of any resolution and much better mimics the natural world. HDR continues its relatively slow growth into real-world use, but continues to show progress.
HDR is so compelling because it can feed our senses more light and it’s no secret that TV shops know we like nice, bright pictures on our TV sets. But the reality of production in HDR is that you have to contend with human eyes which have a great ability to see dark and bright images – but not at the same time. The total ability of the eye to simultaneously distinguish brightness is about 12 stops, which is only two thirds of its non-simultaneous total range.
The fact that our eyes constantly adapt and, let’s face it, interpret what they see, makes understanding brightness in videos tricky. There are dependencies on overall brightness of a picture at any one moment, the previous recent brightness, the brightness of local adjacent parts of the image, the ambient background and much more to consider.
Selios Ploumis steps into this world of varying brightness to creat a ways of quantitatively evaluating brightness for HDR. The starting place is the Average Picture Level (APL) which is what the SDR world uses to indicate brightness. With the greater dynamic range in HDR and the way this is implemented, it’s not clear that APL is up to the job.
Stelios explains his work in analysing APL in SDR and HDR and shows the times that simply taking the average of a picture can trick you into seeing two images as practically the same, whereas the brain clearly sees one as more ‘bright’ than the other. On the same track, he also explains ways in which we can work to differentiate signals better, for instance taking in to account the spread of the brightness values as opposed to APL’s normalised average of all pixels’ values.
The talk wraps up with a description of how the testing was carried out and a summary of the proposals to improve the quantitive analysis of HDR video.
As HDR continues its slow march into use, its different forms both in broadcast and streaming can be hard to keep track of and even differentiate. This talk from the Seattle Video Tech meetup aims to tease out these details.
Brian Alvarez from Aamzon Prime Video starts with a very brief look at how HDR has been created to sit on top of the existing distribution formats: HLS, DASH, HEVC, VP9, AV1, ATSC 3.0 and DVB. The way it does this is in a form based on either HLG or PQ.
Brian takes some time to discuss the differences between the two approaches to HDR. First off, he looks at HLG which is an ARIB standard freely available, though still with licencing. This standard is, technically, backwards compatible with SDR but most importantly doesn’t require metadata which is a big benefit in the live environment and simplifies broadcast. PQ, then, is next when we hear about the differences in approach from HLG and suggests that this gives better visual peformance than HLG. In the PQ ecosystem, Brian works through the many standards explaining how they differ and we see that the main differences are in in colour space and bit-depth.
The next part of the talk looks at the, now famous, venn diagrams showing which copmanies/products support each variant of HDR. This allows us to visualise and understand the adoption of HDR10 vs HLG for instance, to see how much broadcast TV is in PQ and HLG, to see how the film industry is producing exclusively in PQ and much more. Brian comments and gives context to each of the scenarios as he goes.
Finally a Q&A session talks about displays, end-to-end metadata flow, whether customers can tell the difference, the drive for HDR adoption and a discussion on monitors for grading HDR.
HDR and wide colour gamuts are difficult enough in professional settings – how can YouTube get it right with user-generated content?
Viewing conditions have been a challenge right from the beginning of TV but ever more so now with screens of many different shapes and sizes being available with very varied abilities to show brightness and colour. Steven spends some time discussing the difficulty of finding a display suitable for colour grading and previewing your work on – particularly for individual users who are without a large production budget.
Interestingly, we then see that one of the biggest difficulties is in visual perception which makes colours you see after having seen bad colours look much better. HDR can deliver extremely bright and extremely wrong colours. Steven shows real examples from YouTube of where the brain has been tricked into thinking colour and brightness are correct but they clearly are not.
Whilst it’s long been known that HDR and WCG are inextricably linked with human vision, this is a great insight into tackling this at scale and the research that has gone on to bring this under automated control.
This talk is from Streaming Tech Sweden, an annual conference run by Eyevinn Technology. Videos from the event are available to paid attendees but are released free of charge after several months. As with all videos on The Broadcast Knowledge, this is available free of charge after registering on the site.
Software Engineer, YouTube Player Infrastructure
In some parts of the industry UHD is entirely absent. Thierry Fautier is here to shine a light on the progress being made around the globe in deploying UHD.
Thierry starts off by defining terms – important because Ultra HD actually hides several, often unmentioned, formats behind the term ‘UHD’. This also shows how all of the different aspects of UHD, which include colour (WCG), HDR, audio (NGA) and frame rate to name only a few, fit together.
There’s then a look at the stats, where is HDR deployed? How is UHD typically delivered? And the famed HDR Venn diagram showing which TVs support which formats.
As ever, live sports is a major testing ground so the talk examines some lessons learnt, and features a BBC case study, from the 2018 World Cup. Not unrelated, there is a discussion on the state of UHD streaming including discussion of CMAF.
Leading nicely onto Content Aware Encoding (CAE), which was also in use at the world cup.