Resolution Tutorial

Understanding video surveillance resolution can be 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.

For example, in IPVM testing, the human eye is roughly equal to a 10MP resolution camera.

Historically, video surveillance used a similar test chart 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.

You can do that. For example, we did just such a chart based test, and found 720p cameras to be roughly equal to 500 'lines', 1080p roughly 900 'lines', etc. as shown in the image below:

However, manufacturers almost always use pixel count instead of line count for resolution.

Moreover, lines counted was always done in perfectly even lighting conditions. However, with direct sunlight or low light, the resolving power would change, 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 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.

For example, a 1080p resolution camera is commonly described as having 2MP (million pixel) resolution because the sensor used has ~2 million pixels on it (technically usually 2,073,600 pixels as that is the product of 1920 horizontal x 1080 vertical pixels). The image of an imager below shows this example:

Pixels Determine Potential, Not Quality

Pixels are a necessary, but not sufficient, factor for capturing details. Without a minimum number of pixels for a given area / target, it is impossible. See our tutorial on why Pixels Determine Potential, Not Quality.

Limitations

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

Common Surveillance Resolutions

The table below summarizes the most common resolutions used in production video surveillance deployments today. Note that VGA is no longer common except in thermal cameras, but is included here for reference of what 'standard definition' refers to.

Changes For 2019

While 1080p, 4MP, 4K, and other resolutions remain in common use in 2019, there are some notable changes in camera resolution in the past year.

• 3MP/5MP confusion: Historically, users have known 3 and 5MP resolutions as 4:3 aspect ratio (2048x1536 and 2560x1944, respectively). But now, cameras using 16:9 variants of these resolutions are available, delivering increased horizontal PPF, but reducing height of the coverage area, which may eliminate areas visible when using 4:3 cameras.
• 10MP uncommon: Though it used to be one of the most common "high" resolutions, 10MP 4:3 resolution (3648x2752) has practically fallen out of use.
• 6MP available: Finally, 6MP cameras are now readily available, due to new generations of sensors using this resolution. 6MP uses an odd (for surveillance) 3:2 aspect ratio. 

720p cameras, once most popular by a wide margin, have sharply declined as higher resolution options have come down in price and several manufacturers offer fewer or no new models in this resolution compared to higher options.

Resolution Vs. Cost

Everything else equal, higher resolution cameras generally cost more than lower cost models, though pricing for some 4K cameras have started to decline in 2017. Higher prices are due in part to simple increases in component costs adding up, such as more expensive image sensors, additional processors required, higher resolving power lenses, etc. 

However, note that this higher cost does not always result in higher performance, as advanced features such as super low light and true WDR are not always supported or as high performing in higher resolution models, or requiring a significant increase in cost. For example, 1080p cameras most commonly offer strong WDR and super low light options, with such features becoming less common in higher resolution cameras.

Sensor Resolution vs. Stream Resolution

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 multiple cases:

• Limited camera capabilities: In some cases, manufacturers may use readily available sensors of one resolution but crop the sensor to a lower pixel count due to limitations in processing at full resolution. For example, a 6MP sensor may be cropped to 5MP in order to stream at higher frame rates or apply WDR or higher gain levels.
• Panoramic cameras: Second, manufacturers often crop unused portions of the sensor from panoramic camera streams, so a "12MP" fisheye model may actually stream at 8-9MP. See our report Beware Imager vs Stream Resolution for more information on this issue.
• Reduced in software: Finally, an installer may explicitly or mistakenly set 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).

Because of these issues, users should be sure to check not only the resolution of the sensor but the stream resolutions supported and used, typically found lower down the camera's datasheet:

Compression Impact On Resolution

Because resolution most often simply means pixel count, no consideration is given to how much 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, surveillance video is compressed, with that 1080p/30fps stream more typically 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 big one — how much is the video compressed?

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 savings on hard drive costs (less storage required for similar durations), server configuration (less CPU required is required to store less bandwidth), and switches (copper gigabit switches may be used instead of fiber 10GbE).

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. Here is an example:

For full coverage of these details, see our video quality / compression tutorial. 

Also important for considering compression is that manufacturers default compression settings vary significantly, for more see: IP Camera Manufacturer Compression Comparison.

Angle Of Incidence Is Key

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 as he is simply not facing the camera.

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 Overkill

Historically, surveillance has been starved for resolution, with almost always too little for its needs. Anyone familiar with suspect photos on their local news can see this:

However, as the amount of pixels has increased to 1080p and beyond, the opposite issue presents itself: unnecessarily high resolution for the scene. 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.

Additional Factors Impacting Resolution

Finally, note that beyond issues discussed above, many other factors impact surveillance resolution beyond pixels, including:

• Low light performance
• WDR performance
• Compression settings
• Camera angle / downtilt
• Lens selection
• Lens 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.

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[Note: The tutorial was originally written in 2012 but was revised in 2016 and 2019 to show more images / examples and updated resolutions.]