Understanding video surveillance resolution is surprisingly difficult and complex. While the word 'resolution' seems self-explanatory, its use in surveillance is far from it. In this tutorial, we will explain 5 critical elements:

• What resolution traditionally means – seeing details - and the constraints of this approach
• What resolution usually means in surveillance – pixels – and the limits of using this metric
• How sensor and stream resolutions may vary
• How compression impacts resolution greatly
• What limits resolution's value

Resolution – Seeing Details

In normal English and general usage, resolution means the ability to resolve details – to see or make them out. For example, can you read the lowest line on an eye chart? can the camera clearly display multiple lines side by side on a monitor? etc. It is a performance metric focusing on results.

Historically, video surveillance used this approach. Analog camera resolution was measured with line counts, literally the camera's ability to display more lines side by side in a given area on a monitor.

If you could see more lines, it meant you could see more real world details – facial features, characters, license plates, etc.

The main limitation was that resolving power – lines counted – was always done in perfectly even lighting conditions. However, with direct sunlight or low light, the resolving power would change, likely falling significantly. Even more challenging, some cameras fared far worse in these challenging lighting conditions than others.

While this approaches measures performance, it only does so in the most ideal, and often unrepresentative, conditions.

Resolution – Pixel Count

Now, with the shift to IP, manufacturers do not even attempt to measure performance. Instead, resolution has been redefined as counting the number of physical pixels that an image sensor has.

The presumption is that more pixels, much like higher line counts, delivers higher ‘quality’. However, this is far from certain.

Just like with classic resolution measurements that used only ideal lighting conditions, measuring pixels alone ignores the impact of common real world surveillance lighting challenges. Often, but not always, having many more pixels can result in poorer resolving power in low light conditions. Plus, cameras with lower pixel counts but superior image processing can deliver higher quality images in bright sunlight / WDR scenes.

Nonetheless, pixels have become a cornerstone of specifying IP video surveillance. Despite its limitations, you should:

• Recognize that when a surveillance professional is talking about resolution, they are almost certainly referring to pixel count, not resolving power
• Understand the different resolution options available

The table below summarizes the most common resolutions used in production video surveillance deployments today:

Everything else equal, you should expect to pay more for higher resolution (i.e. pixel count) cameras. While these cameras can often deliver more details, keep in mind performance variances (low light, WDR).

Resolution – Sensor vs. Stream

While manufacturers typically specify cameras based on the resolution (i.e. pixel count) of the sensor, sometimes, the resolution of the stream sent can be less. This happens in 2 cases:

• The manufacturer uses a higher resolution sensor than maximum stream they support. One common example of this is panoramic cameras where a 5MP sensor may be used but only a 2MP max output stream is available.
• The integrator explicitly or mistakenly sets a camera to a lower resolution. Some times this is done to save bandwidth but other times it is simply an error or glitch in the VMS default resolution configuration. Either way, many times an HD resolution may look ‘terrible’ but the issue is simply that it is not set to its max stream resolution (i.e., a 3MP camera set to 640 x 480).

Make sure to check not only the resolution of the sensor but the stream resolutions supported and used.

Don’t Forget Compression

Since resolution now measures physical pixels, it does not consider how much the pixels are compressed. Each pixel is assigned a value to represent its color, typically out of a range of ~16 million (24 bits), creating a huge amount of data. For instance, a 1080p/30fps uncompressed stream is over 1Gb/s. However, with digital video today, surveillance video is almost always compressed. That 1080p/30fps stream would more typically be recorded at 1Mb/s to 8Mb/s – 1/100^th to 1/1000^th less than the uncompressed stream. The only question – and it is a huge one – is how much does video get compressed?

The positive side is the potential to massively reduce bandwidth/storage without significantly impacting visible image quality. That is why it is nearly universally done.

However, picking the right compression level can be tricky. How much compression loss can be tolerated often depends on subjective preferences of viewers or the details of the scene being captured. Equally important, increasing compression can result in great cost saving on hard drive, switch and server reductions.

Just because two cameras have the same resolution (i.e. pixel counts), the visible image quality could vary substantially because of differences in compression levels chosen. Read our video quality / compression tutorial to dig into these details.

Limitations on Resolution Value

Even if quality increased exactly in proportion to pixel count (which it obviously does not), two other important limits exist in practical usage: angle of incident and resolution needed.

Angle of Incident

Regardless of how high quality an image is, it needs to be at a proper angle to 'see' details of a subject, as cameras cannot see through walls nor people. For instance:

Even if the image on the left had 10x the pixels as the one on the right, the left one is incapable of seeing the full facial details of the subject. This is frequently a practical problem in trying to cover a full parking lot with a single super high resolution camera. Even if you can get the 'right' number of pixels, if a car is driving opposite or perpendicular to the camera, you may not have any chance of getting its license plate (similarly for a person's face).

Resolution Needed / Overkill

Typically and historically, surveillance has been starved for resolution, with almost always too little for its needs. However, as the amount of pixels increases to 2MP and beyond, frequently this can be overkill. Once you have enough to capture facial and license plates details, most users get little practical benefit from more pixels. The image might look 'nicer' but the evidentiary quality remains the same. This is a major consideration when looking at PPF calculations and ensuring that you do not 'waste' pixels.

Factors Impacting Resolution

Unfortunately, many factors impact surveillance resolution, far beyond pixels, such as:

• Low light performance
• WDR performance
• Compression settings
• Camera angle
• Lens selection and focus

Do not accept specified resolution (i.e. pixel count) as the one and only quality metric as it will result in great problems. Understand and factor in all of these drivers to obtain the highest quality for your applications.