The goal of video delivery is simple — deliver a consistent, quality, viewing experience that satisfies the end-user, one that makes them say, “That’s a fantastic picture.”

The problem is that for far too long, internet broadcast quality has been determined not by what the viewer thinks, but by what each stakeholder in the delivery chain thinks they need in order to satisfy their own narrow idea of quality.

“The filmmaker would say, ‘Let’s jam in more pixels.’ The delivery service would say, ‘Let’s move more bits per second.’ The manufacturer of the viewing device, they’d be interested in pixels and resolution and brightness,” says Dr. Abdul Rehman, SSIMWAVE CEO and co-founder.

And who, or what, is looking out for the overall interest of the poor viewer at the end of the chain? Who makes sure the optimal combination of bits and pixels delivers the highest quality possible? That’s the question begging for answer. And that’s where SSIMWAVE comes in.

“What’s lacking in the industry is we don’t’ have anything to find that compromise point,” says Dr. Rehman’s colleague and mentor, Prof. Zhou Wang, SSIMWAVE’s Chief Science Officer. “We don’t have any tool to tell us: What is the best balance of all these factors that amount to the right thing to deliver a particular video?”

“SSIMWAVE is solving that problem.”

SSIMWAVE’s technology aims to mimic the human visual system, providing video delivery specialists with a real-time dashboard that factors in quality metrics along the delivery chain, giving engineers the information they need to ensure that quality of a video transmission remains consistent and ultimately renders a product that the viewer will recognize as excellent.

“The real problem is not agreeing that quality is important, rather the problem is the misconception about what you mean by quality,” says Prof. Wang.

“The big mistake the whole video distribution industry makes is thinking that bit rate equals quality. This is so wrong. It’s a major mistake.”

When video is transmitted over a broadband network, compromises and trade-offs must be made. A high bit rate helps quality, but costs bandwidth. Compression saves bandwidth ­– and therefore money — but costs quality. And the problem of quality control is subject to further complexities based on the type of program being delivered — live sports versus a movie, for example — and the kind of camera that generated the image and the device that renders it.

All these variables mean that if you were to compress two different video types, send them down the same pipe, one might be of extremely high quality. And the other?

“Complete crap,” says Prof. Wang.

A smart monitoring system, one that sees the way a human being sees, is able to tell the difference

That key difference is why SSIMWAVE eschews bit rate, or the number of pixels, as a sole metric of quality. Measuring bit rate, counting pixels, is easy, but neither delivers information that’s truly useful as a quality metric because there are too many other factors at play that can affect the quality outcome.

Measuring quality from the point of view of what a human being would see, on the other hand, is useful, particularly if the goal is to make a human audience happy.

“People,” Wang says, “trust their eyes.”

And that’s why SSIMWAVE’s technology focusses on mimicking the human visual system. It’s consistent. And it’s correct.

“It’s a complicated thing to capture quality,” says Dr. Rehman. “The goal is to put all of these [variables and factors] into a Viewer Score. That score reflects what viewers, in general, would say when they look at content.”

A video distribution system that can’t consistently and predictably measure quality and adjust for quality is certain to deliver a product that is uneven. The upshot is that resources are then allocated unevenly, delivering, in some cases, good quality; delivering, in others, poor. That, in turn, means money is being spent in an uneven, haphazard, fashion.

“Some people receive very high video quality, others very low,” says Wang. “They may pay the same money or different money in each of those cases, but it’s not proportional. It’s out of control because of the lack of a quality measurement.

“Ideally, you would pay more and get more quality. What we have today in most cases is far from that: In some cases, money is being wasted.”

By doing subjective testing, by measuring quality consistently and accurately, SSIMWAVE is able to help those in the delivery chain ensure that the proper resources are brought to bear at the right moment, ensuring money is spent in a manner that generates a product that is consistent.

“Once you can measure quality, then you can talk about resource allocation,” says Wang. “We figure out, on average, that when you do [certain] things, make certain adjustments, you can deliver quality and save money.”

“In many places, video delivery companies are spending more than they need. In others, where there’s low quality, they should allocate more resources. But on average, you should be able to save money.”

“So [our system] helps our customers spend smarter.”

Better quality. Better predictive metrics. Better resource allocation.

Says Wang: “That’s what we call the revolutionary solution.”