2 Mega Pixels

[Cassaundra Marley]

Acamera sensor is also said to have pixels. In this context, a pixel refers to the number of photosites on a sensor. Photosites are the individual sensing areas that capture light, which is then translated into pixels through software.

The important value for photographers is the number of effective megapixels. This is the number of megapixels that will be in your full-size image when you open up your Raw developer or export a JPEG at maximum size.

If you shoot Raw (and you should), these are combined by your Raw editor through a process called demosaicing to produce what you see when you open a Raw file. If you shoot JPEG, then the camera does the demosaicing.

However, if there were only as many photosites as the final number of desired pixels, then the edges would not have enough photosites for accurate color information. For example, this is what happens when you try and compute color values only from the edge pixels:

In the example on the right, there are 44 or 16 color photosites. Usually, the value of each pixel is computed using four photosites. But when you get to the end of the row, there are only two photosites for the fourth pixel of that row. Therefore, to get a 44 grid of pixels in the final image, you actually need a 55 grid of photosites so each of the 44 pixels has full color information. (I simplified this process a little bit. In reality, the demosaicing stage typically uses a better algorithm than I just outlined.)

However, these additional edge pixels are not enough to account for all the extra pixels. In fact, most cameras have pixels that are completely obscured from light! You can think of them as pixels with black paint on them. These are the so-called optically black pixels. Why should there be pixels on the sensor that cannot even sense light?

Unfortunately, even in total darkness, a sensor will still generate a signal (the dark signal) that will be translated into something other than pure black. This is undesirable, because obviously you want black to register as black.

This correction is typically derived from a model that depends on temperature, which in turn is estimated from the optically black pixels. In practical terms, the hotter your sensor, the more unwanted signal (noise) comes through, and the camera estimates this via these extra pixels to account for it.

A similar technique is used in long-exposure noise reduction, where a dark frame is taken either manually or by the camera to reduce noise. Unfortunately, not all noise can be predicted from the optically black pixels (nor can hot pixels), which is why dark frame subtraction is still useful for long exposures.

As you can see, the number of megapixels you need becomes insane as the print size goes up. I guess everybody who wants to make large prints should go out now and buy the Fuji GFX 100S, right? Well, not exactly. The number of pixels you need is also dependent on the typical viewing distance!

From these considerations, I recommend the following: If you are happy keeping your prints at most 1624 inches, almost any modern sensor will be fine (since the entry point on cameras today is usually at least 20MP). So, this means any recent micro four thirds, APS-C camera, or low-resolution full-frame camera will suffice.

Even if you lack a bit of resolution for a print at your desired PPI, you can use software methods that can do advanced upscaling. Some cameras like the Panasonic GH6 also have pixel-shift or high resolution modes that are suitable for some subjects and provide more resolution. For example, my Panasonic G9 has a pixel-shift mode that produces an 80MP Raw image, which works well as long as everything in the frame is completely stationary.

On the other hand, if you want to print 2436 or higher, you will have more freedom with a high-resolution full-frame sensor like that in the Nikon Z7, Canon R5, or Sony A1. An even higher resolution full-frame camera, like the Sony a7R IVA, which has 61MP, is an excellent choice for those who need to make massive prints.

The second consideration is cropping, which in some cases is unavoidable. As a wildlife photographer for instance, I am often cropping because not all species are easy to get close to. Cropping is also common in macro photography, because the size of the subject in the photo is often limited by the maximum magnification of the macro lens.

So for shooters who use need to crop substantially, I would recommend the higher megapixel bodies like the Canon R5 over lower megapixel ones like the Canon R6. Looking at the print chart above, the 45MP of the Canon R5 will give many more print options. Even after a 1.5x crop, the 45MP of the Canon R5 will still leave you 20MP, whereas the 20MP of the Canon R6 will become 8.9MP.

A pixel is the fundamental building block of an image, and generally, the more pixels, the better. However, photographers are very lucky with modern cameras because most of them have more than enough pixels for almost any situation. For very large printing and cropping, it is definitely worthwhile to have more pixels, and so cameras in the 40-60MP range can be very useful. However, even a 20MP camera can make a very nice large print, and fewer pixels should not hold you back. I look forward to hearing how 100MP is the ultimate level of photography in the comments!

Jason Polak is a bird and wildlife photographer from Ottawa, Canada. He has been interested in photography ever since he received a disposable film camera as a small child. His career as a mathematician led him to move to Australia in 2016, where he started seeing colorful parrots. A few casual shots with a lens completely unsuitable for birds got him hooked, and now wildlife photography is his biggest passion. Jason loves to show the beauty of animals to the world through photography, and one of his lifelong goals is to photograph five thousand species of birds. You can see more of Jason's work on his website or on his YouTube channel.

Thanks for the detailed post.

But what is missing is the consideration of the other side of the shot.

Example: If I have a detail resolution of 1 mm at 20 MP and f/50 mm, I need 80 MP at f/25 mm for the same detail resolution! Or I have to halve the distance.

I was reading about current smartphones and recalled articles by Nasim Mansurov pointing out how it was cellphones that were driving the camera industry. Computational photography advances were the way of the future, he observed, and he sure was right. Cellphones destroyed the point and shoot market, and now do amazing things that flagship mirrorless cameras cannot.

Nasim seems to have vanished from the website he created and brought to excellence.

His influence and voice are sorely missed.

Is he associated with Photography Life anymore? What is he doing? Will we hear from him again?

The algorithms in camera do nothing worth mentioning, if you shoot RAW. After focusing and selecting exposure (shutter/apperture/iso) and pressing the release. RAW data is captured, no demosaicing, no denoising, nothing is done with the data (maybe settings and a thumbnail jpg are added).

Yes, that is very true! Since the aspect ratio of most (all?) cameras is not 16:9, an image will have to be cropped to fit on a 16:9 monitor and so your greater megapixel counts will be needed from the source to account for cropping.

In digital imaging, a pixel (abbreviated px), pel,[1] or picture element[2] is the smallest addressable element in a raster image, or the smallest addressable element in a dot matrix display device. In most digital display devices, pixels are the smallest element that can be manipulated through software.

Each pixel is a sample of an original image; more samples typically provide more accurate representations of the original. The intensity of each pixel is variable. In color imaging systems, a color is typically represented by three or four component intensities such as red, green, and blue, or cyan, magenta, yellow, and black.

In some contexts (such as descriptions of camera sensors), pixel refers to a single scalar element of a multi-component representation (called a photosite in the camera sensor context, although sensel 'sensor element' is sometimes used),[3] while in yet other contexts (like MRI) it may refer to a set of component intensities for a spatial position.

Software on early consumer computers was necessarily rendered at a low resolution, with large pixels visible to the naked eye; graphics made under these limitations may be called pixel art, especially in reference to video games. Modern computers and displays, however, can easily render orders of magnitude more pixels than was previously possible, necessitating the use of large measurements like the megapixel (one million pixels).

The concept of a "picture element" dates to the earliest days of television, for example as "Bildpunkt" (the German word for pixel, literally 'picture point') in the 1888 German patent of Paul Nipkow. According to various etymologies, the earliest publication of the term picture element itself was in Wireless World magazine in 1927,[8] though it had been used earlier in various U.S. patents filed as early as 1911.[9]

Some authors explain pixel as picture cell, as early as 1972.[10] In graphics and in image and video processing, pel is often used instead of pixel.[11] For example, IBM used it in their Technical Reference for the original PC.

Pixilation, spelled with a second i, is an unrelated filmmaking technique that dates to the beginnings of cinema, in which live actors are posed frame by frame and photographed to create stop-motion animation. An archaic British word meaning "possession by spirits (pixies)", the term has been used to describe the animation process since the early 1950s; various animators, including Norman McLaren and Grant Munro, are credited with popularizing it.[12]

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