Skip to main content
Cisco Meraki Documentation

Understanding Image Quality on the MV93

Overview

This article will help you understand image quality on the MV93: why is it different from the fixed dome cameras such as a MV63 and a second generation fisheye like a MV32, and how to make sure you’re getting the best images.

You may also want to refer to the MV93 Installation Guide for placement guidelines on where to deploy fisheye cameras for best results.

The rest of this article requires a basic understanding of cameras. For a basic introduction to MV cameras, read our article, Meraki MV Cameras - Introduction and Features.

What Affects the MV93 Image Quality?

 

The MV93 is the widest of all wide angle lenses along with the MV32, which means that it can see way more of a scene than any other camera. As a result, an object seen through an MV93 is a smaller part of the image compared to the same object through a regular dome camera. The MV93 is great for use cases that require a wide field of view and overall context, while other cameras are better for use cases that require a higher level of detail. 

 

MV63 quality.jpegMV93Xstarro_image_quality.jpg

                                        MV63@4MP with 102° FoV                                                                             MV93@2880x2880 with 180° FoV

The rest of this article will discuss how the MV93’s sensor resolution and field of view affect the image quality, and the different settings that can be adjusted to get the best results as well as a comparison to the second generation of our fisheye camera.

Summary: MV93 vs. Other Gen3 MV Cameras

For any camera, there are fixed camera specifications and user-configurable settings that affect quality. For the MV93, the most important fixed camera specifications are:

  • Sensor resolution, which determines what image resolutions are available

  • Lens focal length, which dictates the camera’s field of view (FoV)

 

The table below outlines these specifications on the second generation MV cameras, showing how the MV93 differs from the other cameras. 

 

Specification

Resulting Image

Sensor Resolution

 

Though the MV93 has a 12.4MP sensor and the MV63 has a 8.41MP sensor, the usable sensor resolutions for all the cameras are essentially equivalent. 

MV63: 8.41MP

8.41MP with almost all 8.4MP usable due to 16:9 aspect ratio

image10.png

 

MV93: 12.4MP

12.4MP but effectively only ~8.3MP usable due to 1:1 aspect ratio

Screenshot 2023-07-04 at 8.40.46 PM.png

Lens Focal Length

 

Although the usable sensor resolution for the MV63 and 93 cameras are basically equivalent, the MV93 covers a much larger field of view, and so a specific object will be captured using less total pixels (characterized by PPF). 

MV63: 102o

Amount of detail decreases linearly the further you go from the camera

MV63IQ.jpeg

Digitally zoomed-in shot of the "Camera sign"

Screenshot - MV12N for MV32 Comparison - Nov 14 2019 044712 PM PST.png

MV93: 180o

Amount of detail decreases at a faster rate the further you go from the camera

MV93IQ.jpeg

Digitally zoomed-in shot of the "Camera sign"

Screenshot - 5th Floor Coffee Bar - 360 - Nov 12 2019 013632 PM PST.png

The configured image resolution and the FoV are then used to estimate the resulting pixels-per-foot (PPF) of a subject at a certain distance and angle from the camera. PPF is a good gauge of quality, but there are a number of other user-configurable settings that can affect this as well. 

The rest of this document will go into more detail on how sensor resolution and PPF affect MV93 image quality, and will cover what other user-configurable settings can affect image quality. 

 

Note: This will not cover the inherent camera hardware specifications and settings like sensor size, pixel size and image tuning, because these are not relevant to a camera end-user. 

More Details on Image Quality

Understanding Sensor Resolution (vs. Image Resolution)

The primary setting that affects quality is image resolution. Image resolution refers to the number of pixels being used to store the details in your scene. A higher resolution generally means better quality due to increased pixels. 

 

The camera’s sensor resolution dictates the maximum image resolution that you can achieve on a camera image. It is indicated in terms of “MP” or megapixels (106 pixels). For example, a 4MP image sensor (2688 horizontal x 1520 vertical pixels at 16:9 aspect ratio) can never create an image with 8MP resolution, but can create images at 4MP, 2MP (1080p or 1920 x 1080 pixels) or 1MP (720p or 1280 x 720 pixels) - all equal or lower image resolutions.

 

The MV93 has an 12.41MP sensor, while the MV63 has a 8.4MP sensor. Although the MV93 has a higher sensor resolution, the maximum number of pixels used for the MV93 is 2880 x 2880 = ~8.3MP effective sensor resolution, which is comparable to the 8.4MP sensor resolution for the MV63.

The reasoning for this is explained in the following paragraphs. 

 

Sensor resolution is an estimate of the total available pixels in the area of the image sensor. It is computed by multiplying [horizontal pixel count x vertical pixel count]. In the image below, you can see that the sensor of the MV63 is composed of 3854x2176 pixels = 8386304 pixels = ~8.4MP. 

image10.png

Note that this sensor already has the 16:9 aspect ratio typically found in many image resolutions (including 720p, 1080p and 4K). Due to this, the entire 8MP (3840 x 2160) can be used to capture an image with a 16:9 aspect ratio; this image would have a 8MP image resolution. However, to achieve a different aspect ratio (4:3 instead of 16:9), some pixels would be left unused to accommodate the different shape in the image sensor. 

 

Screenshot 2023-07-04 at 9.29.53 PM.png

MV93 Sensor Resolution

Compared to the previously described image resolution options the MV93 has a differently sized sensor. In the image below, you can see that the sensor of the MV93 is composed of 4072x3046 pixels = 12,403,312 pixels = ~12.4MP. Note that this sensor has a 16:9 aspect ratio. However, a 360-degree camera will form a circular image, which is best enclosed in a 1:1 aspect ratio. To obtain this, the image can theoretically only utilize at most 3046 pixels in both horizontal and vertical directions. 

 

Note: Due to distortion at the far edge of the lens, the MV93 in this example has cropped a few pixels from the end and is exposing a maximum image resolution of 2880 x 2880 as well as 2112x2112 and 1080 x 1080 downsampled options.

Screenshot 2023-07-04 at 9.44.18 PM.pngScreenshot 2023-07-04 at 9.47.41 PM.png

                                                    Screenshot 2023-07-04 at 9.54.10 PM.png

 

In conclusion, although the MV93 has an 12.4MP sensor, the maximum number of pixels used for the MV93 would be 2880 x 2880 = ~8.3MP effective sensor resolution, which is comparable to the 8.4MP sensor resolution for the MV63. This still does not imply that the quality of the same subject as viewed through both cameras will be comparable. The field of view of the MV93 will drastically affect how much detail the camera can see. The following section uses the concept of pixels-per-foot (PPF) to demonstrate this.  

              clipboard_e6053721d11f04751a7959b39b7790e17.png    image10.png

Using Pixels-per-Foot (PPF) to Estimate Quality

The lens focal length is what dictates the camera’s field of view (FoV). A shorter focal length generally means larger FoV. One way FoV affects image quality is by the rate at which the amount of detail decreases the farther you get from the camera. 

“Detail” on images can be quantified by the concept of pixels-per-foot or PPF. Assuming ideal conditions and good image tuning, it is a great way to compare the quality you would get for a subject at different distances as viewed through different cameras. You can read through the section, Other User-Configurable Settings, bwlow if you want to know what user-configurable settings you can modify to produce closer to ideal conditions and image tuning and therefore more accurate PPF calculations.

It can be computed as follows:

PPF = horizontal pixels / FoV width (in feet)

This implies that you can get a higher PPF (more detail) by:

  • Increasing horizontal pixels

  • Decreasing field of view width

On the MV93, the field of view is fixed at 180o so the only way you can increase PPF is by using a higher image resolution.

 

Because the field of view width for an object viewed through an MV93 camera will be higher than if the same object was viewed through an MV63, the PPF for the MV93 will generally be lower as well.

 

[BETTER] MV63 @ 102o FoV

MV93 @ 180o fixed FoV

Screenshot - MV63MikeW - Jul 04 2023 073539 PM PDT.jpg Screenshot - MV93Xstarro - Jul 04 2023 073606 PM PDT.jpg

Horizontal Pixels

You can improve your PPF by increasing horizontal pixels below. You can do this by using a higher image resolution. The horizontal pixels for each image resolution available on MVs are underlined below.

 

Resolution

Horizontal x Vertical

720p

1280 x 720 pixels

1080p

1920 x 1080 pixels

1080x1080

1080 x 1080 pixels

2560 x 1440 2560 x 1440 pixels
2112x2112 2112 x 2112 pixels
2880x2880 2880 x 2880 pixels
4K 3840 x 2160 pixels

FoV Width

FoV width is a result of the camera’s FoV, which is dictated by its lens focal length. It is essentially the physical distance that will be captured by the horizontal pixels in the image resolution. 

For example: This image is a 4K image, so the horizontal pixel width is 3840. One can measure the FoV width by finding the distance between something at the far left of the image (for example, the pink shoes on the left of the image below) up to something on the far right of the image (like the white strip that runs along the length of the wall) . Note that PPF is in feet, the PPF of this image is about 3840 pixels / 10.7 feet  = 358 PPF

Screenshot - MV63X - Jul 06 2023 123630 PM PDT.jpg

Example PPFs

Here is a set of images with different PPF values.( All images are taken at 5x digital zoom )

35PPF

48PPF

[BEST] 71PPF

MV63_1080p_high_SS.png

MV63_4MP_high_SS.png

MV63_4k_enhanced_SS.png

Notice how the same distance produces different PPFs in these examples, and especially how the PPF is much smaller for the fisheye cameras. A good rule of thumb is that faces are usually distinguishable around ~50 PPF, so if you want that level of detail, the fisheye camera might not be enough.( depending on the mounting height)

 

Camera Type

Resolution

Horizontal x Vertical

Distance

FoV width

PPF

Distance

FoV width

PPF

Normal

720p

1280 x 720 pixels

10 feet

10 ft

128

15 feet

~15ft

~85

Normal 1080p 1920 x 1080 pixels 10ft 192 ~15ft ~128

Super Telephoto

1080p

1920 x 1080 pixels

5ft

384

~7.5ft

~256 

Normal 4MP 2560 x 1440 pixels 10ft 256 ~15ft ~170

Fisheye

1080x1080

1080 x 1080 pixels

~63ft

~17

~94ft

~11.5

Fisheye 2112x2112 2112 x 2112 Pixels ~63ft ~33.5 ~94ft ~22.5
Fisheye 2880x2880 2880 x 2880 Pixels ~63ft ~45.7 ~94ft ~30
Normal 4MP 2560 x 1440 pixels ~10ft 256 ~15ft ~170
Normal 4k 3840 x 2160 pixels ~10ft 384 ~15ft ~256

Calculating PPFs

It is sufficient to understand the relationship between PPF, resolution and FoV to conclude that the MV93 image quality will often be inferior to that of other cameras. 

However, in cases were you have a target PPF, this section below shows how you can calculate PPFs. You can then work backwards and determine what camera would be sufficient.

For example, a nice rule of thumb is that faces are usually distinguishable around ~50 PPF and you would like to see if the MV93 would provide sufficient detail for subjects around the main area of the camera (depending on the resolution you prefer)

 

  1. What is the image resolution?

    • Let’s assume you are going to use 2560 horizontal pixels. 

  2. What is your target PPF?

    • 50PPF

  3. Compute the ideal FoV width.

    • 50PPF = 2560 / FoV width, so FoV width = 2560 / 50 =  51.2 feet

  4. Compute the FoV width you can obtain with the MV93 and compare. 

    • It is difficult to directly measure the field of view width. However, if you are able to use a measuring tape to estimate this, you can use that.

    • However, it may be simpler to use the distance of the subject from the center of the camera to estimate this FoV width as shown below.

      • For normal cameras with a triangular field of view (MV63), the FoV width can be calculated accurately using trigonometry (fun!) but is usually estimated as equal to the distance from the camera for normal cameras and half for super telephoto cameras.

      • For 360 degree cameras with a circular field of view (MV93, MV32), the FoV width is the circumference (2*pi*radius), where the radius is the distance from the center of the camera (see the diagram below that illustrates this). This means that PPF decreases at a rate of 2*pi for fisheyes. 

        • At the same distance from the camera (for example = 1), the resulting PPF can be up to ~6.28 times lower for a 360-degree camera (2*pi = 6.28) compared to a normal camera.

 

image22.png

 

Let’s suppose we care about capturing enough detail for faces of people where the camera sign is placed, 13 feet from the camera. This produces a FoV width of 81.6 feet. This is larger than 51.2, so the MV93 is likely not going to provide the right amount of detail. However, if the objects are 51.2 / 6.28 = ~8.15 feet away, it should be sufficient. Alternatively, you can use a camera with a smaller field of view, that can produce a FoV smaller than 51.2, as in the 63 below.

 

[BETTER]  MV63 (PPF = ~71)


MV93, zoomed in (PPF = ~22)
MV63_4k_enhanced_SS.png MV93_2880_SS.png

 

With this knowledge, you can make better judgments about the level of detail that the MV93 can provide for a particular use case. 

Other User-Configurable Settings to Optimize Image Quality 

 

Please note that PPF is not a perfect metric and can be affected by a myriad of other things like focus, bitrate (which is affected by the compression of the video) and the enablement of other capture modes such as HDR (high dynamic range) and IR mode. 

Here are some examples of user-configurable settings that would help optimize your image quality even further.

  • Quality (bit rate, frame rate and compression)

    • Quality (as defined on the Meraki Dashboard) is essentially the bitrate and the frame rate. A lower bitrate will have more compression which may cause loss in detail in some pixels in order to save bandwidth. A lower frame rate may cause blurriness in some moving objects. Note that cameras will have different compression technology such as H.264, H.265, SmartCodec etc, which influences how low the bit rate can go for a specific scene. 

 

In the example below, you can see that there is a slight reduction in detail in the smiley face, and more noise around the edges of the sign. 

 

Better Quality

Worse Quality

4k at Enhanced Quality (8000kbps at 15fps)

((these shots were zoomed in for comparison)

4k at Standard Quality (4500kbps at 8fps)

(these shots were zoomed in for comparison)

 

MV63_4k_enhanced_SS.png

 

MV63_4k_standard_ss.png

 

  • High Dynamic Range (HDR)

    • This image correcting feature will allow both bright and dark areas of your image to be properly exposed, with better detail. 

In the example below, you can note that you can better discern the details of the lights and the back conference room with HDR on. Please note that HDR works best ONLY when there is a bright source of light in the frame like a door/window or a light directly shining on the camera for afar.

 

Better Quality of the Back Conference Room & Overhead Lights

Worse Quality of the Back Conference Room & Overhead Lights

With High Dynamic Range

(these shots were zoomed in for comparison)

No High Dynamic Range

(these shots were zoomed in for comparison)

Screen Shot 2019-11-12 at 2.37.42 PM.png

image12.png

  • Was this article helpful?