Video: Banding Impairment Detection

It’s one of the most common visual artefacts affecting both video and images. The scourge of the beautiful sunset and the enemy of natural skin tones, banding is very noticeable as it’s not seen in nature. Banding happens when there is not enough bit depth to allow for a smooth gradient of colour or brightness which leads to strips of one shade and an abrupt change to a strip of the next, clearly different, shade.

In this Video Tech talk, SSIMWAVE’s Dr. Hojat Yeganeh explains what can be done to reduce or eliminate banding. He starts by explaining how banding is created during compression, where the quantiser has reduced the accuracy of otherwise unique pixels to very similar numbers leaving them looking the same.

Dr. Hojat explains why we see these edges so clearly. By both looking at how contrast is defined but also by referencing Dolby’s famous graph showing contrast steps against luminance where they plotted 10-bit HDR against 12-bit HDR and show that the 12-bit PQ image is always below the ‘Barten limit’ which is the threshold beyond which no contrast steps are visible. It shows that a 10-bit HDR image is always susceptible to showing quantised, i.e. banded, steps.

Why do we deliver 10-bit HDR video if it can still show banding? This is because in real footage, camera noise and film grain serve to break up the bands. Dr. Hojat explains that this random noise amounts to ‘dithering’. Well known in both audio and video, when you add random noise which changes over time, humans stop being able to see the bands. TV manufacturers also apply dithering to the picture before showing which can further break up banding, at the cost of more noise on the image.

How can you automatically detect banding? We hear that typical metrics like VMAF and SSIM aren’t usefully sensitive to banding. SSIMWAVE’s SSIMPLUS metric, on the other hand, has been created to also be able to create a banding detection map which helps with the automatic identification of banding.

The video finishes with questions including when banding is part of artistic intention, types of metrics not identifiable by typical metrics, consumer display limitations among others.

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Speakers

Dr. Hojat Yeganeh Dr. Hojat Yeganeh
Senior Member Technical Staff,
SSIMWAVE Inc.

Video: Broadcast Fundamentals: High Dynamic Range

Update: Unfortunately CVP choose to take down this video within 12 hours of this article going live. But there’s good news if you’re interested in HDR. Firstly, you can find the outline and some of the basics of the talk explained below. Secondly, at The Broadcast Knowledge there are plenty of talks discussing HDR! Here’s hoping CVP bring the video back.

Why is High Dynamic Range is like getting a giraffe on a tube train? HDR continues its ascent. Super Bowl LIV was filmed in HDR this year, Sky in the UK has launched HDR and many of the big streaming services support it including Disney+, Prime and Netflix. So as it slowly takes its place, we look at what it is and how it’s achieved in the camera and in production.

Neil Thompson, an Sony Independent Certified Expert, takes a seat in the CVP Common Room to lead us through HDR from the start and explain how giraffes are part of the equation. Dynamic Range makes up two thirds of HDR, so he starts by explaining what it is with an analogy to audio. When you turn up the speakers so they start to distort, that’s the top of your range. The bottom is silence – or rather what you can hear over the quiet hiss that all audio systems have. Similarly in cameras, you can have bright pixels which are a different brightness to the next which represents the top of your range, and the dithering blacks which are the bottom of your range. In video, if you go too bright, all pixels become white even if the subject’s brightness varies which the equivalent of the audio distortion.

With the basic explanation out of the way, Neil moves on to describing the amount or size of dynamic range (DR) which can be done either in stops, contrast ratio or signal to noise ratio. He compares ‘stops’ to a bucket of water with some sludge at the bottom where the range is between the top of sludge and the rim of the bucket. One stop, he explains, is a halving of the range. With the bucket analogy, if you can go half way down the bucket and still hit clear water, you have 1 stop of dynamic range. If you can then go a quarter down with clean water, you have 2 stops. By the time you get to 1/32nd you have 5 stops. If going to 1/64 of the height of the bucket means you end up in the sludge, your system has 5 stops of dynamic range. Reducing the sludge so there’s clear water at 1/64th the height, which in cameras means reducing the noise in the blacks, is one way of increasing the dynamic range of your acquisition.

Update: Unfortunately CVP choose to take down this video within 12 hours of this article going live. But there’s good news if you’re interested in HDR. Firstly, you can find the outline and some of the basics of the talk explained below. Secondly, at The Broadcast Knowledge there are plenty of talks discussing HDR! Here’s hoping CVP bring the video back.

If you would like to know how lenses fit into the equation of gathering light, check out this talk from Cannon’s Larry Thorpe.

Neil looks next at the range of light that we see in real life from sunlight to looking at the stars at night. Our eye has 14 stops of range, though with our iris, we can see the equivalent of 24 stops. Similarly, cameras use an iris to regulate the light incoming which helps move the restricted dynamic range of the camera into the right range of brightness for our shot.

Of course, once you have gathered the light, you need to display it again. Displays’ ability to produce light is measured in ‘nits’, which is the amount of light per metre squared. Knowing how many nits a displays helps you understand the brightness it can show with 1000 nits, currently, being a typical HDR display. Of course, dynamic range is as much about the blacks as the brightness. OLED screens are fantastic at having low blacks, though their brightness can be quite low. LEDs, conversely, Neil explains, can go very bright but the blacks do suffer. You have to also take into account the location of a display device to understand what range it needs. In a dim gallery you can spend longer caring about the blacks, but many places are so bright, the top end is much more important than the blacks.

With the acquisition side explained, Neil moves on to transmission of HDR and it’s like getting a giraffe on a tube train. Neil relates the already familiar ‘log profiles’. There are two HDR curves, known as transfer functions, PQ from Dolby and HLG (Hybrig Log Gamma). Neil looks at which profiles are best for each part of the production workflow and then explains how PQ differs from HLG in terms of expressing brightness levels. In HLG, the brightest part of the signal tells the display device to output as brightly as it can. A PQ signal, however, reserves the brightest signal for 10,000 nits – far higher than displays available today. This means that we need to do some work to deal with the situation where your display isn’t as bright as the one used to master the signal. Neil discusses how we do that with metadata.

Finishing off the talk, Neil takes questions from the audience, but also walks through a long list of questions he brought along including discussing ‘how bright is too bright?’, what to look for in an engineering monitor, lighting for HDR and costs.

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Speakers

Neil Thompson Neil Thompson
Freelance Engineer & Trainer

Video: HDR Formats and Trends

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. Whilst HDR has long been held up as a perfect example of ‘better pixels’ and many have said they would prefer to deploy HD video plus HDR rather than moving in to UHD at the same time as introducing HDR, few have followed through.

Brian Alvarez from Amazon 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 is next, and we hear about the differences in approach from HLG with the suggestion that this gives better visual performance 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 (by Yoeri Geutskens) showing which companies/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.

Watch now! / Download the Slides

Speaker

Brian Alvarez Brian Alvarez
Principal Product Manager,
Amazon Prime Video

Video: User-Generated HDR is Still Too Hard

HDR and wide colour gamuts are difficult enough in professional settings – how can YouTube get it right with user-generated content?

Steven Robertson from Google explains the difficulties that YouTube has faced in dealing with HDR in both its original productions but also in terms of user generated content (UGC). These difficulties stem from the Dolby PQ way of looking at the world with fixed brightnesses and the ability to go all the way up to 10,000 nits of brightness and also from the world of wider colour gamuts with Display P3 and BT.2020 (WCG).

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.

Watch now!
Free registration required

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.

Speaker

Steven Robertson Steven Robertson
Software Engineer, YouTube Player Infrastructure
Google