The Megapixel Race And Its Clear Winner

Like any Moore’s Law-inspired race, the megapixel race in digital cameras in the late 1990s and into the 2000s was a harsh battleground for every manufacturer. With the development of the smartphone, it became a war on two fronts, with Samsung eventually cramming twenty megapixels into a handheld. Although no clear winner of consumer-grade cameras was ever announced (and Samsung ended up reducing their flagship phone’s cameras to sixteen megapixels for reasons we’ll discuss) it seems as though this race is over, fizzling out into a void where even marketing and advertising groups don’t readily venture. What happened?

The Technology

A brief overview of Moore’s Law predicts that transistor density on a given computer chip should double about every two years. A digital camera’s sensor is remarkably similar, using the same silicon to form charge-coupled devices or CMOS sensors (the same CMOS technology used in some RAM and other digital logic technology) to detect photons that hit it. It’s not too far of a leap to realize how Moore’s Law would apply to the number of photo detectors on a digital camera’s image sensor. Like transistor density, however, there’s also a limit to how many photo detectors will fit in a given area before undesirable effects start to appear.

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CMOS Image Sensor Mechanism Illustration, By User:たまなるたみ – drawing created myself, GPL, https://commons.wikimedia.org/w/index.php?curid=371238. Note that each pixel has its own amplifier.

Image sensors have come a long way since video camera tubes. In the ’70s, the charge-coupled device (CCD) replaced the cathode ray tube as the dominant video capturing technology. A CCD works by arranging capacitors into an array and biasing them with a small voltage. When a photon hits one of the capacitors, it is converted into an electrical charge which can then be stored as digital information. While there are still specialty CCD sensors for some niche applications, most image sensors are now of the CMOS variety. CMOS uses photodiodes, rather than capacitors, along with a few other transistors for every pixel. CMOS sensors perform better than CCD sensors because each pixel has an amplifier which results in more accurate capturing of data. They are also faster, scale more readily, use fewer components in general, and use less power than a comparably sized CCD. Despite all of these advantages, however, there are still many limitations to modern sensors when more and more of them get packed onto a single piece of silicon.

While transistor density tends to be limited by quantum effects, image sensor density is limited by what is effectively a “noisy” picture. Noise can be introduced in an image as a result of thermal fluctuations within the material, so if the voltage threshold for a single pixel is so low that it falsely registers a photon when it shouldn’t, the image quality will be greatly reduced. This is more noticeable in CCD sensors (one effect is called “blooming“) but similar defects can happen in CMOS sensors as well. There are a few ways to solve these problems, though.

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A sunrise picture taken with an entry-level DSLR at 1600 ISO. At this sensitivity, noise in the clouds can be seen in the form of random fluctuations of some pixels. This effect would be mitigated by a camera with a larger sensor, a lower sensor sensitivity with a longer shutter speed (which would blur the turbine blades) or a scene with more light. Photo  © 2016 by Bryan Cockfield

 

First, the voltage threshold can be raised so that random thermal fluctuations don’t rise above the threshold to trigger the pixels. In a DSLR, this typically means changing the ISO setting of a camera, where a lower ISO setting means more light is required to trigger a pixel, but that random fluctuations are less likely to happen. From a camera designer’s point-of-view, however, a higher voltage generally implies greater power consumption and some speed considerations, so there are some tradeoffs to make in this area.

Another reason that thermal fluctuations cause noise in image sensors is that the pixels themselves are so close together that they influence their neighbors. The answer here seems obvious: simply increase the area of the sensor, make the pixels of the sensor bigger, or both. This is a good solution if you have unlimited area, but in something like a cell phone this isn’t practical. This gets to the core of the reason that most modern cell phones seem to be practically limited somewhere in the sixteen-to-twenty megapixel range. If the pixels are made too small to increase megapixel count, the noise will start to ruin the images. If the pixels are too big, the picture will have a low resolution.

There are some non-technological ways of increasing megapixel count for an image as well. For example, a panoramic image will have a megapixel count much higher than that of the camera that took the picture simply because each part of the panorama has the full mexapixel count. It’s also possible to reduce noise in a single frame of any picture by using lenses that collect more light (lenses with a lower f-number) which allows the photographer to use a lower ISO setting to reduce the camera’s sensitivity.

Gigapixels!

Of course, if you have unlimited area you can make image sensors of virtually any size. There are some extremely large, expensive cameras called gigapixel cameras that can take pictures of unimaginable detail. Their size and cost is a limiting factor for consumer devices, though, and as such are generally used for specialty purposes only. The largest image sensor ever built has a surface of almost five square meters and is the size of a car. The camera will be put to use in 2019 in the Large Synoptic Survey Telescope in South America where it will capture images of the night sky with its 8.4 meter primary mirror. If this was part of the megapixel race in consumer goods, it would certainly be the winner.

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LSST Image Sensor, By Todd Mason, Mason Productions Inc. / LSST Corporation – https://www.lsst.org/sites/default/files/photogallery/Camera_CU-full.jpg, CC BY-SA 4.0, https://commons.wikimedia.org/w/index.php?curid=52230238

With all of this being said, it becomes obvious that there are many more considerations in a digital camera than just the megapixel count. With so many facets of a camera such as physical sensor size, lenses, camera settings, post-processing capabilities, filters, etc., the megapixel number was essentially an easy way for marketers to advertise the claimed superiority of their products until the practical limits of image sensors was reached. Beyond a certain limit, more megapixels doesn’t automatically translate into a better picture. As already mentioned, however, the megapixel count can be important, but there are so many ways to make up for a lower megapixel count if you have to. For example, images with high dynamic range are becoming the norm even in cell phones, which also helps eliminate the need for a flash. Whatever you decide, though, if you want to start taking great pictures don’t worry about specs; just go out and take some photographs!

(Title image: VISTA gigapixel mosaic of the central parts of the Milky Way, produced by European Southern Observatory (ESO) and released under Creative Commons Attribution 4.0 International License. This is a scaled version of the original 108,500 x 81,500, 9-gigapixel image.)

A Compact Star Tracking Tripod

The next giant leap for mankind is to the stars. While we are mostly earthbound — for now — that shouldn’t stop us from gazing upwards to marvel at the night sky. In saying that, if you’re an amateur astrophotographer looking to take long-exposure photos of the Milky Way and other stellar scenes, [Anthony Urbano] has devised a portable tracking setup to keep your photos on point.

When taking pictures of the night sky, the earth’s rotation will cause light trails during long exposures. Designed for ultra-portability, [Urbano’s] rig uses an Arduino UNO controlled Sanryusha P43G geared stepper motor coupled to a camera mounting plate on a small tripod. The setup isn’t designed for anything larger than a DSLR, but is still capable of taking some stellar pictures.

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Kinect And Raspberry Pi Add Focus Pulling To DSLR

Prosumer DSLRs have been a boon to the democratization of digital media. Gear that once commanded professional prices is now available to those on more modest budgets. Not only has this unleashed a torrent of online content, it has also started a wave of camera hacks and accessories, like this automatic focus puller based on a Kinect and a Raspberry Pi.

For [Tom Piessens], the Canon EOS 5D has been a solid platform but suffers from a problem. The narrow depth of field possible with DSLRs makes it difficult to maintain focus on subjects that are moving relative to the camera, making follow-focus scenes like this classic hard to reproduce. Aiming for a better system than the stock autofocus, [Tom] grafted a Kinect sensor and a stepper motor actuator to a Raspberry Pi, and used the Kinect’s depth map to drive the focus ring. Parts are laser-cut, including a nice enclosure for the Pi and display that makes the whole thing reasonably portable. The video below shows the focus remaining locked on a selected region of interest. It seems like movement along only one axis is allowed; we’d love to see this system expanded to follow a designated object no matter where it moves in the frame.

If you’re in need of a follow-focus rig but don’t have a geared lens, check out these 3D-printed lens gears. They’d be a great complement to this backwoods focus-puller.

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Building A Full-Spectrum Digital Camera On The Cheap

The sensor on your digital camera picks up a lot more than just the light that’s visible to the human eye. Camera manufacturers go out of their way to reduce this to just the visible spectrum in order to produce photos that look right to us. But, what if you want your camera to take photos of the full light spectrum? This is particularly useful for astrophotography, where infrared light dramatically adds to the effect.

Generally, accomplishing this is just a matter of removing the internal IR-blocking filter from your camera. However, most of us are a little squeamish about tearing into our expensive DSLRs. This was the dilemma that [Gavin] faced until a couple of years ago when he discovered the Canon EOS-M.

Now, it’s important to point out that one could do a similar conversion with just about any cheap digital camera and save themselves a lot of money (the practically give those things away now). But, as any photography enthusiast knows, lenses are just as important as the camera itself (maybe even more so).

photo-31So, if you’re interested in taking nice pictures, you’ve got to have a camera with an interchangeable lens. Of course, if you’re already into photography, you probably already have a DSLR with some lenses. This was the case for [Gavin], and so he needed a cheap digital camera that used Canon interchangeable lenses like the ones he already had. After finding the EOS-M, the teardown and IR-blocking filter removal was straightforward with just a couple of hiccups.

When [Gavin] wrote his post in 2014, the EOS-M was about $350. Now you can buy them for less than $150 used, so a conversion like this is definitely into the “cheap enough to tinker” realm. Have a Nikon camera? The Nikon 1 J3 is roughly equivalent to the original EOS-M, and is about the same price. Want to save even more money, and aren’t concerned with fancy lenses? You can do a full-spectrum camera build with a Raspberry Pi, with the added benefit of being able to adjust what light is let in.

3D Printed Lens Gears For Pro-grade Focus Pulling

Key Grip, Gaffer, Best Boy – any of us who’ve sat through every last minute of a Marvel movie to get to the post-credits scene – mmm, schawarma! – have seen the obscure titles of folks involved in movie making. But “Focus Puller”? How hard can it be to focus a camera?

Turns out there’s a lot to the job, and in a many cases it makes sense to mechanize the task. Pro cinematic cameras have geared rings for just that reason, and now your DSLR lens can have them too with customized, 3D printed follow-focus gears.

Gear_Selection_01_full_render_preview_featuredUnwilling to permanently modify his DSLR camera lens and dissatisfied with after-market lens gearing solutions, [Jaymis Loveday] learned enough OpenSCAD to generate gears from 50mm to 100mm in diameter in 0.5mm increments for a snug friction fit. Teamed up with commercially available focus pulling equipment, these lens gears should really help [Jaymis] get professional results from consumer lenses. 

Unfortunately, [Jaymis] doesn’t include any video of the gears in action, but the demo footage shown below presumably has some shots that were enabled by his custom gears. And even if it doesn’t, there are some really cool shots in it worth watching.

And for the budding cinematographers out there without access to a 3D printer, there’s always this hardware store solution to focus pulling.

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Vintage Lens On A Modern Camera

Sometimes you get plain lucky in multiple ways, enabling you to complete a hack that would otherwise have seemed improbable. [Mario Nagano] managed to attach a vintage 1950’s lens to a modern mirrorless camera (translated from Portuguese).

Photographers tend to collect a lot of gear and [Mario] is no exception. At a local fair in Sao Paolo, he managed to pick up a Voigtlander Bessa I – a bellows camera (or folding camera). It came cheap, and the seller warned him as much, commenting on the bad external shape it was in. But [Mario] had a sharp eye, and noticed that this was a camera that would have remained closed most of the time, due to its construction.

Inspection showed that the bellows was intact. What excited and surprised him was the excellent Color-Skopar objective mounted on a Prontor-S trigger, which is considered premium compared to the entry level Vaskar lens. His plan was to pick up another Voigtlander Bessa-I with a better preserved body, but the cheaper lens and do a simple swap. He never did find another replacement though. Instead, he decided to fix the excellent vintage lens to a DSLR body.

He’d read about a few other similar hacks, but they all involved a lot of complicated adapters which was beyond his skills. Removing the lens from the vintage camera was straightforward. It was held to the body by a simple threaded ring nut and could not only be removed easily, but the operation was reversible and didn’t cause any damage to the old camera body. The vintage lens has a 31.5mm mounting thread while his Olympus DSLR body had a standard 42mm thread. Fabricating a custom adapter from scratch would have cost him a lot in terms of time and money. That’s when he got lucky again. He had recently purchased a Fotodiox Spotmatic camera body cap. It’s made of aluminium and just needed a hole bored through its center to match the vintage lens. There’s no dearth of machine shops in Sao Paolo and it took him a few bucks to get it accurately machined. The new adapter could now be easily fixed to the old lens using the original 31.5mm ring nut.

The lens has a 105mm focal length, so the final assembly must ensure that this distance is maintained. And he got lucky once again. He managed to dig up a VEB Pentacom M42 macro bellows from an old damaged camera. Was it worth all the effort ? Take a look at these pictures here, here and here.

Automated Weatherproof Timelapse System With DSLR And Raspberry Pi

[madis] has been working on time lapse rigs for a while now, and has gotten to the point where he has very specific requirements to fill that can’t be done with just any hardware. Recently, he was asked to take time lapse footage of a construction site and, due to the specifics of this project, used a Raspberry Pi and a DSLR camera to take high quality time lapse photography of a construction site during very specific times.

One of his earlier rigs involved using a GoPro, but he found that while the weatherproofing built into the camera was nice, the picture quality wasn’t very good and the GoPro had a wide-angle lens that wouldn’t suit him for this project. Luckily he had a DSLR sitting around, so he was able to wire it up to a Raspberry Pi and put it all into a weatherproof case.

thumbOnce the Pi was outfitted with a 3G modem, [madis] can log in and change the camera settings from anywhere. It’s normally set up to take a picture once every fifteen minutes, but ONLY during working hours. Presumably this saves a bunch of video editing later whereas a normal timelapse camera would require cutting out a bunch of nights and weekends.

The project is very well constructed as well, and [madis] goes into great detail on his project site about how he was able to build everything and configure the software, and even goes as far as to linking to the sites that helped him figure out how to do everything. If you’ve ever wanted to build a time lapse rig, this is probably the guide to follow. It might even be a good start for building a year-long time lapse video. If you want to take it a step further and add motion to it, check out this time lapse motion rig too!