Video: Extension to 4K resolution of a Parametric Model for Perceptual Video Quality

Measuring video quality automatically is invaluable and, for many uses, essential. But as video evolves with higher frame rates, HDR, a wider colour gamut (WCG) and higher resolutions, we need to make sure the automatic evaluations evolve too. Called ‘Objective Metrics’, these computer-based assessments go by the name of PSNR, DMOS, VMAF and others. One use for these metrics is to automatically analyse an encoded video to determine if it looks good enough and should be re-encoded. This allows for the bitrate to be optimised for quality. Rafael Sotelo, from the Universidad de Montevideo, explains how his university helped work on an update to Predicted MOS to do just this.

MOS is the Mean Opinion Score and is a result derived from a group of people watching some content in a controlled environment. They vote to say how they feel about the content and the data, when combined gives an indication of the quality of the video. The trick is to enable a computer to predict what people will say. Rafael explains how this is done looking at some of the maths behind the predicted score.

In order to test any ‘upgrades’ to the objective metric, you need to test it against people’s actual score. So Rafael explains how he set up his viewing environments in both Uruguay and Italy to be compliant with BT.500. BT.500 is a standard which explains how a room should be in order to have viewing conditions which maximise the ability of the viewers to appreciate the pros and cons of the content. For instance, it explains how dim the room should be, how reflective the screens and how they should be calibrated. The guidelines don’t apply to HDR, 4K etc. so the team devised an extension to the standard in order to carryout the testing. This is called ‘subjective testing’.

With all of this work done, Rafael shows us the benefits of using this extended metric and the results achieved.

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Rafael Sotelo Rafael Sotelo
Director, ICT Department
Universidad de Montevideo

Video: Towards Measuring Perceptual Video Quality & Why

In the ongoing battle to find the minimum bitrate for good looking video, automation is key to achieving this quickly and cheaply. However, metrics like PSNR don’t always give the best answers meaning that eyes are still better the job than silicon.

In this talk from the Demuxed conference, Intel’s Vasavee Vijayaraghavan shows us examples of computer analysis failing to identify lowest bitrate leaving the encoder spending many megabits encoding video so that it looks imperceptibly better. Further more it’s clear that MOS – the Mean Opinion Score – which has a well defined protocol behind it continues to produce the best results, though setting up and co-ordinating takes orders of magnitude more time and money.

Vasavee shows how she’s managed to develop a hybrid workflow which combines metrics and MOS scores to get much of the benefit of computer-generated metrics fed into the manual MOS process. This allows a much more targeted subjective perceptual quality MOS process thereby speeding up the whole process but still getting that human touch where it’s most valuable.

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Vasavee Vijayaraghavan Vasavee Vijayaraghavan
Cloud Media Solutions Architect,