IP Camera Manufacturer Compression Comparison

Author: Derek Ward, Published on Feb 21, 2014

Compression is very important. While resolution gets the attention, compression is critical and can be a silent killer - both for quality and bandwidth.

Regardless of resolution, all surveillance video is compressed. And even if 2 cameras have the same resolution, their compression levels can be much different. [See our compression / quality tutorial for background.]

Thankfully, compression in H.264 is standardized on a scale of 0 to 51, as shown in the image below:


However, camera manufacturers almost never disclose Q levels used. Instead, they use a variety of homemade scales and naming systems. Here is a sample of ones we tested inside:

So you can have 2 manufacturer's cameras with the same resolution but significantly different compression levels, and therefore varying image quality and bandwidth consumption.

An industry first, IPVM has analyzed each of these manufacturers and answered these key questions:

  • What is the real H.264 quantization level for each camera manufacturer's default settings? How do they vary? Who defaults the lowest and highest?
  • To normalize the H.264 quantization levels so that each manufacturer had the same compression, what camera settings should be used?
  • How does the range of compression levels used for each manufacturer map to H.264 quantization levels?
  • What is the impact of bandwidth as H.264 quantization / compression levels are varied for different manufacturers?

If you really care about image quality and optimizing bandwidth / storage use, this is a critical report.

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Comments (11)

Interesting.

Just mention that some manufacturers you forgot here, offer in addition to "pre defined quality values" some Manual settings where you can enter 0 to 51 customized values...so you get "settings for dummies " or "more accurate professionnal settings"

All this impact bandwidth IF you chose VBR output. If not, the output will be stable but you'd better chose the good CBR level to stand your Fps x resolutionxQuality choices. If not, the quality/Compression will become even worst (most of the time you keep the frame rate and downgrade quality ) This is whatoften happen by night ...and dark times ...brrrr

So you first think you will get a 28 quality , but finally you get a 35 or 40 and some pixelised fps where you can not identify your target... oups

Yes, this presumes the use of VBR, which is the typical default in IP cameras today. As you say, if you use CBR, by definition, bit rate will remain fixed but quantization level will vary depending on the scene.

Background: CBR vs VBR: Surveillance Streaming

Another great test, very informative.

John it would be very intersting to do a survey on who is using VBR or CBR. are you sure VBR will win in North America ? and worldwide ?

Most guys I know put CBR.. VBR +Cap is close to CBR but even worst if the limit is too low because hyper compressing before limitA part of Axis other vendors propose Fixed Quality, but most without a Cap, so it's seen as too risky for your storage, especially by Night.

Last survey with 60% VBR is strange .... next survey should ask also which brands are deployed...

I am pretty sure all 8 cameras in this test default to VBR (or VBR + a high cap).

You mean a survey of integrator selection (i.e. VBR vs CBR) or manufacturer defaults?

I think CBR is a really bad move for almost anyone and VBR + Cap is better. VBR + Cap allows the camera to stream at lower bit rates when the scene is less complex / hard to compress yet go up to whatever high point you choose. By contrast, CBR is wasting bandwidth for all times except for when the scene needs that set bit rate.

Derek, truly a commendable addition to the IPVM canon!

Thanks for the quiz, and here's a couple questions for you in return:

How was the Q measured, what tools, what method (mean average)?

Do you have a high confidence level in these numbers?

Mainly the section on Compression Impact on Bandwidth, arguably the most critical section, seems to present more questions than it answers.

I understand and acknowledge your disclaimer regarding the dangers of generalizing the data, but even granting that, there are some wildly divergent data points that should be explained if at all possible.

Take the Sony and the Samsung, witb the Samsung stream only getting slightly smaller with a q change of 6 where Sony gets almost 4x as small? These cameras are roughly equivalent hardware wise at least, so what is really going on? Like the frame rate changing? Or the profile?

More data would be helpful here to identify anomalies, but strangely half the cameras are missing from this chart without any explanation, and the ones we have left are divided between "Sony" behavior and "Samsung" behavior.

Any thoughts welcome.

Hello Rukmini Wilson,

Q was measured using AVInaptic, a free program that analyzes quantization, which we have been using for quite some time now.

As for your questions regarding the bandwidth chart, we wanted to show a trend as a rule of thumb that there is a strong likelyhood that decreasing compression or Q levels will increase bandwidth (Noting that compression is not the only factor in determining bit rate). No other settings such as FPS, resolution, or other codec or camera settings aside from compression/quality levels were changed via the camera's web UI.

Camera selection for the bandwidth section was random, and given the plethora of variables on the impact different cameras and manufacturers have with regards to bandwidth, 4 were chosen.

Could you please expand on what you mean between "Sony" behavior and "Samsung" behavior? What about "Dahua" and "Hikvision" behavior? Those 2 were included as well, no?

Hello.

Could you please provide a brief description of a procedure with which you obtained quantization level? You took 'average DRF'? What kind of files you put in AVInaptic?

Cheers.

See: How to Measure Video Quality / Compression Levels for full explanation of this.

Thanks John - everything clear now.

Thanks for the quick response Derek!

"Sony" behavior is: cameras which show dramatic (4X, 3X) reduction in bandwidth from q of 28 to 22

"Samsung" behavior is : cameras which show pathetic (1.2X, 1.6X) reduction in bandwidth from q of 28 to 22

The are two "Sony" types are the Hika and the Sony itself. The two "Samsung" types are the Dahua and the Samsung itself.

Note: These 4 cameras scored 3x,3x,5x.3x on the reduction from 34 to 28 so for the next set to be wildly divergent is worthy of an explanation. Even though the Sony and the Samsung are roughly equiv cameras hardware wise, to simpify the analysis lets just talk about the Sony by itself for a moment. On the first q setting of 34pass it had a 5x reduction, on the second a 1.2x reduction. Thats quite a difference!

Of course it could be explained by the scene complexity somehow, but then why wouldn't the Samsung also show dramatically less gains at the lower q? Instead we see dramatically higher gains after the lowering of q!.

Remember that although the administration of q thru a particular vendor is quirky and can't be relied upon, the h.264 definition of q is very formal and has to do with combining progressively more spatial frequencies. There are of course many other parameters invlolved in the actual bandwidth savings, like macro block size, and variable q settings between I and b,p frames, but assuming a motionless scene alot of these fall away and q should dominate, one would think.

As for your "strong likelyhood that decreasing compression will increase bandwidth" I would say its only trivially true: you would have been hard pressed with any camera on any scene on any day that would show an increase in compression level causing an increase in bandwidth.

Camera selection for the bandwidth section was random...

"Call it in the air, Heads I take the top-half of the chart, Tails I take the bottom. Tails it is..." :)

As far as the "plethora of variables" reason for only showing 4 cameras, goes, weren't all 8 cameras already set up at varying q levels for the Camera Compression Scales part of the test? It would seem you would just have to measure the bandwidth at that point, no?

In any event lest you misinterpret my musings as an attack, its not. I'm just trying to understand what's causing the data points to diverge. If the variance is inline with your expectations, then I will adjust mine. Thanks.

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