Is 2 megapixels better than original?

The number of megapixels you will need for a security camera depends on the surface area you wish to cover, how clear you need the footage to be, and how much your budget is. The more megapixels your security camera has, the greater level and depth of surveillance and zooming capacity you will have.

So how do you figure all of this out? Let’s break down exactly what you need to consider in deciding what resolution is best for you.

‍

Resolution is a technical term typically used for digital photography and video, and it relates to the technical equivalent to the film grain in analogue photography. During the height of analogue photography, it was said that the lower the number of grain in an image the sharper it was or less “pixelated.”

Resolution is likely to be one of the top features you consider when looking for a good quality security camera as it determines the level of detail that is observed in an image. The number of pixels across the width and the height of an image is called the resolution, so IP security camera resolution is the total number of pixels that make up an image. For example, a very common display resolution for video would be a width of 1920 pixels and a height of 1080 pixels.

There are one million pixels in a megapixel. If you multiply the width and the height of an image you get the total number of megapixels. 1920 pixels multiplied by 1080 pixels equals 2,073,600 so that is a 2MP image. The height of an image is used to symbolise the resolution; you can say 1080p resolution when referencing an image with 2 million megapixels.

‍

Home security cameras come in a range of different resolutions depending on your needs and your budget. The most common ones you will see on the market include 2MP (1080p), 4MP (1440p), 5MP (1920p) and 8MP (4K/2160P).

2MP cameras are already considered high definition (HD) cameras, while those that reach or exceed 8MP fall into the ultra high definition category (UHD). These are the security camera resolutions that are most widely used as they provide a high level of detail. By zooming in on a face or licence plate during filming, the chances of clearly identifying them are high.

When considering the number of megapixels you may need for your camera, first you must consider the spot you will be surveilling. CCTV Solutions can help to determine the best camera for you based on where and what you want to capture.

It’s tempting to want all the best specifications when you’re looking at technical tools and the quality of good CCTV cameras have progressed by leaps and bounds, and with cheaper price tags. Although the standard for a good quality CCTV camera has been 1080 pixels, more and more people are opting for 2k or even 4k resolution. Generally, the higher the security camera resolution, the better the image quality and the details will be clearer. The obvious conclusion is that 4K IP security cameras deliver sharper and clearer images when compared to 1440p, 1080p, and 720p IP security cameras.

The truth is, you can still get high quality imaging with clear details from a distance with 2K security cameras, and they are especially good for monitoring entrances to your home, garages, walkways, front yards, backyards and small businesses.

‍

4K cameras have a much higher resolution of 3840 x 2160p, equalling 8 megapixels, and are at the high end of surveillance video quality. They have a wide field of view and are effective for facial recognition and license plate recognition at greater distances. One of the challenges with 4K security cameras is that they require more bandwidth and space for storage. You will need to keep this in mind when budgeting for your surveillance needs.

On the plus side, if you have the budget for these top range cameras, newer video compression technology is making it possible to further reduce storage consumption. An example of this would be a surveillance camera that features H.265 video encoding. This codec can save up to 50% of available storage space compared to older H.264 encoding.

For some businesses, 4K cameras are a no brainer. If you want to capture footage of the highest possible quality while monitoring larger areas under a single camera, 4K cameras will future proof your video surveillance system.

4K surveillance cameras are best for medium and large businesses, including parking lots, warehouses, retail stores, hotels, restaurants, and other commercial and residential properties.

‍

The human eye is not dissimilar to a camera, but we don’t see in pixels at all. However, if we were to compare, scientist and photographer Dr. Roger Clark assumed that in order to create a screen so sharp that you wouldn’t be able to see individual pixels, you would need 576 million pixels within your field of view. That's 576 megapixels. An incredible thought when you compare it to the 8 megapixels of an UHD security camera.

‍

SnapBridge Help

About SnapBridge

Connecting to the Camera

Downloading Pictures

Viewing Pictures on Your Smart Device

Remote Photography

Bluetooth Remote Control

Sharing Pictures

SnapBridge Tips and Tricks

Using SnapBridge with Cameras That Support the Wireless Mobile Utility (Android Only)

It depends on the camera. Megapixels is just a count of how many photosites there are on the sensor. More photosites doesn't make the camera any better, in fact it can actually have a negative effect.

More often than not, camera manufacturers market their products with their megapixels.

Indeed, the average digital camera resolution is continually increasing.

You can find 20MP sensors in smartphones. With the Sony A7R IV, you can even take 240MP photos by sensor shifting.

But what does the camera resolution mean to you? Do you need a high megapixel count? Today, we’ll find out.

Let’s try to see through the marketing slogans. Megapixel and camera resolution have become catchwords.

It’s cool, indeed, that even your phone is capable of shooting 20-megapixel photos. But how does that translate to real detail? Not so well.

And more importantly, do you need it?

A very general answer is no; you probably don’t.

There are two applications where you do need high resolution: extensive cropping (digital zooming) and large printing. And even in those situations, you need detail, not necessarily high megapixels.

Camera resolution is not equal to pixel count, although they often get mixed up, and used interchangeably. Film also has a resolution – referring to the level of detail it can resolve.

Pixels are the smallest component of a digital camera sensor. They record light. There are millions of them – one by one, and they build a coherent image.

Their number is of importance, but it does not tell us everything about the resolution of a camera.

Pixel count is in the form of megapixels. One megapixel (MP) is one million pixels. So, when someone says a camera has a 20MP camera resolution, they refer to the 20 million pixels on its sensor.

Indeed, pixel count poses a limit to how detailed an image can be. But in itself, it doesn’t set a minimum level for detail. It doesn’t mean anything until we don’t know other factors.

The only thing that a high pixel count surely promises is less moiré.

Camera sensors are rectangular. The pixels on them are not scattered randomly – they are in a grid.

The dimensions of the two sides are comparable. Their aspect ratio ranges from 1:1 (square) to 16:9 in some video-oriented cameras.

The most used aspect ratios are 3:2 and 4:3.

For example, my Canon 5D MkIII has a 3:2 aspect ratio. Its sensor measures 5760 pixels on the long side, and 3840 pixels on the short side.

You can multiply the two sides to get the total pixel count. 5760 x 3840 is equal to ‭22,118,400‬. (So, the 5D MkIII has a 22.1MP sensor.)

I can still achieve different aspect ratios, but only by cropping. That’s also what the camera is doing when I set a different aspect ratio in the menu. Cropping reduces the resolution.

When we say resolution in the context of cameras, we mean spatial resolution. That is the technically correct term, but it’s probably the first and last occasion you’ve read it.

Camera resolution tells us the level of detail cameras can provide. In other words, it’s the “ability of the imaging modality to differentiate two objects” (Wikipedia).

The resolution depends on several factors.

When the recording surface is film, it’s determined by:

In the era of digital sensors, this slightly changes to:

Additionally, external circumstances also influence the clarity of an image.

Let’s discuss some of these in detail.

It’s self-evident that smaller pixels demand better optical quality from a lens.

An 8μm (micrometre) pixel has four times the area and twice the pixel pitch of a 4μm pixel.

This means that if the lens is just sharp enough to provide detail for the 8μm pixels, it will fail to produce enough sharpness for the 4μm pixels.

Now, where can you find small pixels?

In two places:

In turn, the Canon 5D (the original one) has a 12MP pixel count on a full frame sensor. The pixel pitch is 8µm. Its pixels are 36 times bigger than the pixels on the iPhone!

Smaller pixels also mean less light falling onto a single pixel.

However, both large and small pixels need to be brought up to the same level. Otherwise, the image consisting of small pixels would be a lot darker.

This results in more noise because when you brighten an image, you also brighten its noise.

With smaller pixels, diffraction is also more pronounced. It starts to have a noticeable effect at low apertures, sometimes already at f/2.8.

But what is diffraction?

It’s hard to explain diffraction without going very scientific. If you’re an expert in physics – please forgive my simplification.

You’re probably familiar with diffraction in water. When you place a barrier with a small hole in the way of water, the flow bends near the hole. The smaller the hole is, the more bending.

This is what happens with light, too. At smaller apertures (higher f-stops) diffraction harms sharpness and resolution.

Due to diffraction, there is a very measurable, physical limit on resolution. No matter how good your lens is, it’s always true. It’s given with this formula: p = (1.22 λ A) / 2 Here, p is the smallest pixel that can receive pixel-level information from the lens. λ is the wavelength of incoming light, and A is the f/stop.

Let’s calculate with the iPhone XR‘s camera. We open up the aperture all the way to f/1.8 to get the least amount of diffraction.

The wavelength of visible light is about 0.5µm. p = (1.22 * 0.5µm * 1.8) / 2 The resulting p is 1.1µm.

What this means is that the iPhone XR (with its 1.3µm pixel pitch) is very close to being diffraction-limited.

So, even if the lens is optically perfect, free of all aberrations, it’s at its peak. It can’t accommodate smaller pixels.

Take another example.

At f/16, the resulting p is 7.3µm. This means that cameras with a pixel pitch around this value are only affected by diffraction above f/16.

So, the original 5D with its 8µm pixel pitch only gets diffraction-limited after f/16.

This coincides with my experiences. When I use the old 5D, I tend to get away even with f/16 without a decrease in sharpness. On the 5D MkIII and MkIV, it’s more like f/11 and f/9.

Take a look at this illustration I shot with the Canon 5D MkIV and the Canon 100mm f/2.8L macro lens. Both shots are in perfect focus; the softening is due to diffraction.

So, for diffraction to not pose a threat to image resolution, you need to stay at or below f/8 on most cameras.

But wide apertures can also affect sharpness to the worse – especially on cheaper lenses, but lenses generally don’t perform the best wide open.

Please note that here I’m only talking about sharpness and not other aspects of image aesthetics. Sharpness is an important quality of a lens, but not a primary deciding factor, at least for me.

A great measurement of lens sharpness are MTF charts. They show you the resolution of a lens, irrespective of sensor size and pixel count.

But you can check your lenses just in real-life usage, too. In the end, if they are sharp enough for you, you’re good to go.

The upper limit of lens sharpness is pixel-level sharpness. It means that a lens is so sharp it can resolve image data to every single pixel, without affecting the neighbouring pixel.

This not only depends on the lens but also on the pixel pitch of the cameras you use it on.

My 85mm f/1.8 lens is sharp enough to provide pixel-level sharpness on the 12MP Canon 5D.

Not so much on the 30MP Canon 5D MkIV, but it still performs decently there. And I love that lens anyway.

This also proves that smaller pixels demand more from lenses.

Note that when you view both images at the same size (say, on your monitor), you won’t notice a difference. You will only see it when you examine them zoomed-in.

We all know that when light passes through glass, it refracts. But this is not a supernatural power of glass only.

Light refracts in every substance, including air.

You don’t notice it at short distances. It becomes apparent when you shoot far-away subjects with a telephoto lens.

Take a look at this photo. I shot it with a 400mm f/2.8 lens (a bit excessive for this task, I know) at f/8. The closest buildings are 5km (3mi) away, so everything is in focus. But notice the difference between the buildings in the foreground and the hills in the background.

The foreground is nice and sharp. It’s close enough not to be significantly affected by atmospheric blur.

The hills are more than three times further away from the camera. At this distance, the light starts to split. Different wavelengths are differently shifted. This shift causes blur.

Now, I won’t say to go out and buy the highest megapixel camera you can find. Megapixel and pixel count, as I mentioned earlier, mean nothing without the proper settings and technique to support them.

It’s important to note that very often your aim is not to capture the absolute highest amount of detail you could theoretically capture.

Photography is not all about sharpness. It’s about communicating a story or feeling. Or to please aesthetically.

Still, there are applications where you want to highest resolution. It might be that you want to crop it later (“digitally zoom in”). Large prints also require highly detailed images.

So, what can you do to achieve the highest resolution with your photography equipment?

Know your lens. Know it’s sharp and weak points. Examine what apertures it performs best at. Check if close-up focusing results in a blurrier image, this is often an issue. Check sharpness at different focal lengths throughout the zoom range.

Know your camera. Know the ISO levels that you can dial in without affecting the image too much.

Shoot at proper shutter speed. Experiment with shutter speeds at all focal lengths. We all know the inverse focal length rule, but there’s more to it. When I photograph people, I tend not to go slower than 1/400s, to freeze motion. (Unless I want a creative motion blur effect.)

Set it up properly. Set it to full aspect ratio, and best quality JPG. Or, just set it to RAW, so you have more choices when post-processing. Also, check your in-camera sharpening settings. It doesn’t provide more but emphasizes the existing detail. Oversharpening, however, can hurt detail in a photo.

Clean your cameras and lens. Make sure there’s little to no dust in it. If your lens has fungus, get it removed. Clean the sensor.

Check your filters. If you’re using filters, be sure that they don’t degrade image quality. Some cheaper filters tend to decrease sharpness.

Focus accurately. Excercise autofocusing, make it behave how you want it. If necessary, make AF micro-adjustments. Be aware of focus shift in your lens and focus accordingly. If you shoot steady subjects on a tripod, use manual focus.

Be aware of external circumstances. Hazy days, although promising a lot for creative photography, don’t help sharpness.

Be aware of diffraction. Check the pixel pitch on your camera, and try to avoid apertures that are affected by diffraction.

A primary reason for shooting high-detail images is the option to crop in later.

It gives you flexibility and creative freedom. You can change your composition, your main subject, your focal point, and communicate something else by cropping.

Note that “digital zooming” is the same process as cropping, but it happens in-camera, with no option to later reveal cropped out parts. I recommend avoiding the digital zoom. Crop your images during post-processing, instead.

I don’t like shooting with zooms. I appreciate extra light over versatility. So, I often carry just a 24mm and an 85mm lens when traveling.

Most of the time, I change framing by moving closer with the 24mm. It also gives a perspective that I like better.

However, in the photograph below, I had to crop in later. I couldn’t go closer. To be fair, I like both versions equally, but the cropped image places more attention on the boy, and less on the surroundings.

I could do this because I had plenty of resolution.

Upscaling or enlarging small images rarely yields the results you’d like. Adobe Photoshop and other editing programs offer algorithms to make upscaled photos less pixelated, but the outcome is far from sharp.

However, in the past few years, the options became much more sophisticated. This is due to the rise and evolution of machine learning algorithms.

Photoshop‘s tool has improved significantly, but there are web-based services for advanced upscaling.

Check out this video from PiXimperfect to learn more about them.

Also, consider the previous points. A photo that is close to pixel-level sharp is easier to upscale than a blurry, softer one.

The other reason for really high-resolution images is printing.

Now, I don’t mean printing at home with the printer that you use for printing documents.

I mean professional photo printing, magazines, books, and posters.

Printing works similarly to digital imaging. Printers paint tiny dots on the paper – those dots are the smallest unit of detail in printing.

Digital pixels can be directly translated to dots. And just like pixels, dots also don’t tell you a lot about detail.

However, printing services ask for files with specific pixel dimensions. This is because they assume that the files you submit contain pixel-level information, and are detailed.

During printing, there’s a new unit you will encounter: DPI. It stands for dots per inch.

DPI tells you how densely the dots are printed onto the paper. The denser they are, the more detailed the print can be.

Magazines, books and smaller prints look good above 300 DPI, generally.

Posters, larger prints are made with slightly lower dot densities. This is because there’s often not enough resolution for supplying 300 DPI.

Let’s suppose that you’d like an 8″ x 10″ print size. It’s a standard, medium-sized format.

Just multiply the desired DPI (in this case, 300 DPI) with the length of the sides.

It turns out that for this print, you’ll need to submit an image that is 2400 x 3000 pixels.

If you translate that to megapixels, it’s not a lot: only 7.2MP.

Now, make a calculation the other way around. If I use the full pixel count on my 22.1 megapixel camera, what size can I print at different densities?

The images are 5760 x 3840. They have an aspect ratio of 3:2. Let’s see the sizes:

Digital display of images doesn’t require a lot of resolution.

The images that you find on websites are tiny. For example, on our site, we use images that are 700 pixels on their longer side.

That’s still enough for seeing what’s in the image. But it’s also small enough to load quickly.

The full resolution of monitors and TVs is not a lot bigger, either. The most popular display sizes are HD and FullHD, with 4K gaining more and more share.

But what are those exactly?

HD refers to 1280 x 720, or 1366 x 768 pixels. These are around 1 megapixel!

FullHD is twice as large, at 1920 x 1080 pixels. That’s 2 megapixels.

4K is a significant step, it’s four times larger than FullHD, at around 3840 x 2160. It’s close to 8 megapixels.

Higher resolution displays are rare.

What a Bayer filter is

Colour camera sensors use Bayer filters to capture the various colours. The Bayer filter effectively halves the resolution of the sensor for each colour (though green is left with slightly more in a checker-board pattern).

Each pixel on the sensor can only capture either red, green or blue light, but not all three colours. A software algorithm needs to interpolate the data later to re-construct the full resolution photograph in full colour.

Demosaicing

This interpolation process (called demosaicing) will visually restore a lot of the effective lost resolution, making it look pretty sharp again, but it can only do so by taking fairly intelligent guesses. It's not the same as if you had been able to capture the image at full resolution in the first place.

For example, while demosaicing is fairly good at claiming back lost sharpness from the Bayer filter, any fine detail such as hair, comb-like patterns or fine stripes are likely to suffer from aliasing, which can show up as colourful interference patterns:

(source)

(These images show very poor demosaicing algorithms for the sake of illustration. Modern cameras - even cellphones - use much smarter ones.)

Modern demosaicing algorithms are pretty smart and can minimise the effect of aliasing, but it still cannot retain the fine detail. A distant picket fence shot on a 1920x1080 colour sensor will retain less effective resolution than an RGB 1920x1080 image that is computer-generated or scaled down from a larger sensor or scanned on a scanner.

How this affects the resolution

(and how I came up with the "11 megapixels" figure)

The effective resolution of the resulting image after demosaicing doesn't look like it is half the resolution claimed by the sensor, because of the gains made by smart demosaicing routines, and the fact that the green channel, which correlates well with luminance, has more resolution than the other colours.

But it still would need to be shrunk by 50% to remove any loss due to interpolation. If you really wanted to ensure that your picture was "full resolution", without any loss of detail due to interpolation, you would need to have a colour sensor with double the resolution you want, in both the horizontal and vertical direction, and then resample the resulting image to 50%.

In order to capture full effective resolution of 1920x1080, a colour camera sensor (with a Bayer filter, which includes 99% of colour camera sensors) would need to have a resolution of double that: 3840x2160. That's over 8.2 megapixels. Due to cropping on the sensor (again due to the camera's demosaicing method) you'd effectively need around 8.8 megapixels to be sure.

And that's if your sensor had a perfect 16:9 aspect ratio. If your sensor has a 3:2 aspect ratio, you'd need around 10.7 megapixels to capture a 3840x2160 image, including discarded areas on the top and bottom to make up for the aspect ratio, and a small border to account for any demosaicing crop.

Sensors without Bayer filters

While 99% of colour camera sensors use Bayer filters, there are some that use an alternative pixel layout, but the principle is the same.

There are also some colour sensors that don't need a colour filter at all, such as the Fovean X3 sensor, but these are still exceptionally rare and have their own issues. Manufacturers also tend to lie about their pixel count (in order to be competitive with sensors using a Bayer filter, where the pixel count always sounds a lot more impressive than it really is due to the above described filter).

Another alternative that is employed by some expensive professional video cameras is to have three entirely separate sensors, one for each of red, green and blue, and use a light splitter to throw the same image on all three of them. Obviously this cannot exist in a DSLR or compact camera or any normal type of consumer stills camera. But it can explain why pixel counts on the sensors of professional video cameras can't be compared to those on DSLRs.