Jul 27, 2022
Sigma’s CEO Kazuto Yamaki has revealed that the company’s efforts in making a full-frame Foveon sensor are on track to be finished by the end of the year. In an interview published on Sigma’s YouTube Channel, spotted by Mirrorless Rumors , Yamaki was asked if there is any news on the progress of the sensor’s development since the update provided earlier this year. “We are still working on it, and now we are working on the prototype of the three-layer X3 sensor,” he responds. “This sensor should be available sometime this year.”
Yamaki and Sigma have previously said that the process of making a full-frame Foveon sensor has been difficult, and he reiterates that here. “The Foveon X3 sensor is not a very versatile sensor,” Yamaki says. “There are some ‘cons’ like performance in low light, but if there is a good amount of light, that camera can create very beautiful and impressive photos.”
Foveon’s Troubled Development History
Sigma’s Foveon sensors use a proprietary three-layer structure in which red, green, and blue pixels each have their own full layer. In traditional sensors, the three pixels share a single layer in a mosaic arrangement and the camera “fills in” missing colors by examining neighboring pixels. Since each pixel of a photo is recorded in three colors, the resulting photo should be sharper with better color accuracy and fewer artifacts. But Sigma has been struggling to bring a full-frame Foveon sensor to market for years. Originally announced in September of 2018, the full-frame Foveon sensor has seen multiple delays. IN February of 2020, the company announced that the development had been sent “back to the drawing board” and delayed for an unspecified amount of time. A year later, Yamaki revealed that the sensor had been delayed again and could not go into mass production due to a critical flaw . In February of 2022, SIgma announced that it had reached the second of three stages in prototyping the sensor and said that if stage three went well, it could start to verify its mass producibility. “When we proceed to Stage 3, we will verify the mass-producibility of the sensor with research institutes and manufacturing vendors based on the evaluation results, and then make a final decision on whether or not to mass-produce the image sensor,” Yamaki said at the time. “Although we have not yet reached the stage where we can announce a specific schedule for the mass production of the image sensor, we are determined to do our best to realize a camera that will truly please our customers who are waiting for it, as soon as possible.”
Yamaki’s new statements and 2022 timeline seem to indicate that the company has successfully completed that third stage, renewing hope that the full-frame Foveon sensor will see the light of day.

Sigma’s Full-Frame Foveon Sensor Will Be Ready By the End of 2022

UpdatedJun 13, 2022
Timothee Cognard
Back in the early 2000s, Sigma — a company usually known in the photography community as a lens manufacturer — released a new type of camera sensor named the Foveon X3. This sensor technology was first patented in 1999 by a company called Foveon, Inc. (later acquired in 2008 by Sigma) and featured an innovative color perception technology: a 3-layer stack of photosensitive diodes. On paper, this technology promised to outperform CMOS sensors in color accuracy, low-light noise, and image sharpness. This article will explain why, despite being a clever idea, Foveon technology has never really made it in the photographic industry. Back to Basics: How Your Camera Captures Colors
Silicon is widely known as a semiconductor material and is used as such in many electronic circuits. For photographers, however, the main interest in silicon is that it is a photosensitive material. To be more specific, silicon absorbs light for any wavelength comprised between 400nm and 1100nm. The good news is that this range covers the visible light spectrum (400nm to 750nm, roughly) and even a bit of the near-infrared spectrum. The bad news is that silicon by itself does not discriminate between the color of the light and only accumulates any photon in the 400-1100nm range. A first step in improving the image quality is to add a filter to remove the infrared light (between 750nm and 1100nm) before it reaches the sensor. The resulting system constitutes a monochrome camera sensor (providing black and white images). From there on, the most common way to gather some color information is to use a Color Filter Array (CFA). Usually, this filter is organized following a Bayer pattern (from the name of a Kodak engineer) with red, green, green, and blue filters. A profile view of a Bayer filter on an image sensor. Illustration by Cburnett and licensed under CC BY-SA 3.0. Thanks to these three filters, one can recover the color information in the image. However, the process comes at the expense of some image resolution. For a given “red” pixel, one has to make an interpolation to find the missing green and blue information. Many interpolation algorithms exist, but the process always results in some form of color artifact and image softening. Color Filter Arrays, in addition to being inaccurate, also absorb many photons in the process of collecting some color information. The absorption varies depending on the filter choice and image content, but it is generally admitted that the light flux is divided by a factor of 3 before reaching the sensor. That’s 1.5 stops of light. The Clever Idea Behind Foveon Technology
It happens that, depending on its color, a given photon travels a specific distance in silicon before being absorbed. This “travel distance” is related to the energy of the photon, which depends on its wavelength. Short wavelength photons (blue light, UV light, etc.) are more energetic than longer wavelength ones (red light, infrared light, etc.) and thus are absorbed after a shorter journey in silicon. “The absorption depth is the inverse of the absorption coefficient. An absoption depth of, for example, 1 um means that the light intensity has fallen to 36% (1/e) of its original value.” Chart by Christiana Honsberg and Stuart Bowden of ASU. Since absorption depth in silicon provides an estimate of the photon wavelength, the measure of the absorption depth provides theoretically the color information. The clever idea of Foveon sensors is to use “depth filters” instead of side-by-side color filters. Wavelength-dependent absorption in silicon and the Foveon X3 sensor. Illustration by Anoneditor and licensed under CC BY-SA 3.0. On paper, at least, removing any color filter should increase the light flux falling on the sensor and remove the drawbacks associated with color filters. Back when Foveon sensors first reached the market in 2002 in the Sigma SD9 DSLR, most digital cameras were far from 10MPx resolution. The Canon EOS-1D had 4.2MPx and the Nikon D100 had 6MPx. Since color filter arrays require digital interpolation, for a given number of pixels, the color filter array offered a massive sharpness upgrade. Sigma actually tried to market this difference in image quality by claiming that the SD9 camera had a 3.43MP output image but “10.3 million effective pixels,” meaning that their pixels were performing 3 times better. Several academic papers have indeed found that Foveon sensors offered a higher perceived resolution thanks to the lack of interpolation and of color artifact around sharp edges. From this perspective, Foveon sensors provide a clear and measurable benefit to the user. One last point claimed by Sigma is that Foveon sensors outperform color filter sensors when it comes to color accuracy. The claim is explained by the lack of color information interpolation. Indeed, for a given Foveon pixel, the red, green, and blue data are recorded in the same place, contrary to a color filter array. On paper at least, the Foveon sensor has it all: better light flux means better low-light performance, better color accuracy, and better sharpness of the image. But paper specs never quite tell the full story…
What Went Wrong With the Brilliant Foveon Idea? The real question from there on really boils down to this: since the idea behind Foveon sensors is quite clever, why aren’t we all using Foveon sensors? Resolution
Some of the interest in the Foveon technology vanished with the evolution of CMOS sensors. The dramatic increase in pixel density has reduced one of the main selling points of Foveon sensors. Sure, it’s not really an apples-to-apples comparison since pixel counts only contribute to a fraction of the final image quality (along with the lens, the amount of light available, etc). Since even smartphones can deliver at least 20MPx images, Foveon is less attractive than in the early 2000s. Color
The color advantage of the Foveon sensor is theoretically undeniable but offers only little practical benefit. Outside of color-calibrated monitors and laboratory environments, the difference in color accuracy is small enough to go unnoticed by most casual photographers. It certainly is more subtle than the effect of white balance mistakes or creative Instagram filters. The response curves of Bayer (left) and Foveon (right) sensors. Charts via Boris van Schooten . Noise
Here is potentially the most debatable point of all. On paper, Foveon sensors should collect about 3 times more light, which should translate in a 1.7 times improvement in signal to noise ratio. That is, assuming the shot noise is dominant. However, it turns out that in practical comparisons, the low-light performance of Foveon sensors falls short. Even Foveon General Manager Shri Ramaswami admitted it in a 2014 interview :
“One of the limitations of Foveon’s approach is that image noise is higher than in conventional sensors,” he said. “This is probably due in part to inefficiencies within the sensor architecture itself — perhaps some light is lost to internal structures that separate the layers — and also in part to the processing that has to be done to produce pure colors from the rather mixed signals that the chip actually captures.”
CMOS sensors and Foveon sensors share a similar design issue: some of the light leaks from one pixel to the next. In CMOS sensors, this crosstalk problem is solved using vertical isolation structures between the photodiodes . In Foveon sensors, however, it is not possible to apply the same trick (otherwise, you would only get the blue color information). Thus, Foveon sensors tend to suffer from photon leakage from one photodiode layer to the next. Image Processing: The Hidden Problem Behind Unusual Sensors
A drawback that is common to all “unusual” color systems (be it Fuji X-Trans, RGBW filters, or Foveon) is that the image processing is also affected by the choice. Even though Bayer filters might not be the best way to capture colors, they are around for several decades and are absolutely dominant in the sensor market. As a consequence, the incentive is strong for image processing researchers and companies to fine-tune all algorithms for this type of sensor. De-noising, for instance, is usually done with some assumptions about the statistics regarding the collected photons that cannot be directly applied to Foveon sensors. Sadly, given the share of Foveon sensors used, most image processing companies don’t have any incentive to support Foveon files, not to mention developing image processing pipelines dedicated to such sensors. The trend is only getting worse with machine-learning-based algorithms. To put it bluntly, machine-learning algorithms are only as good as the data used to train them (both in terms of quantity and quality). Since there are thousand times more images available from Bayer filter arrays than from Foveon, the former sensors will benefit from better algorithms than the latter. Other Marketing Considerations
Lastly, we need to address the elephant in the room. Photography equipment doesn’t always sell for technical reasons. Pricing, marketing, lens ecosystems, branding — there are many factors in the success of a technology. Sigma has tried to provide a sensor different from anything else, but the company had to fight two battles at the same time. The first one was to prove the image quality of Foveon sensors. The second one was to prove that, as a camera manufacturer, their cameras outperformed Canon or Nikon ones. Foveon could have been Sigma’s secret weapon in the competitive camera industry. But, the performance difference between traditional and Foveon sensors is not clear cut. Not clear enough, at least, to attract new photographers to the Sigma brand. Will the Foveon Sensor Even Return? Sigma has started developing a full-frame Foveon sensor , and the project is in an early prototype stage according to Sigma’s latest statement. It seems likely that the project could remain stuck in the prototype phase and never reach the market. At best, from this calendar, it seems unrealistic to expect a mass-produced sensor before 2024. As a company, Sigma has a good and well-deserved reputation for lens manufacturing and would like to extend its business further into cameras and sensors. However, a camera is far more than just a sensor. The real challenge for Sigma might very well be the lack of high-quality Image Processing. Sigma even had to create a plugin for Adobe Photoshop in order to get Foveon files opened. While it isn’t impossible that Sigma releases a new camera with a full-frame Foveon sensor, there is still a long way to go in selling the technology outside of the existing Foveon community, let alone making it an industry standard. About the author: Timothee Cognard is an optical expert and photographer based in Paris, France.

Foveon: The Clever Image Sensor That Has Failed to Catch On

Feb 22, 2022
Roughly Three Stages of Initial Development
Sigma’s CEO Kazuto Yamaki explains that the development of the three-layer image sensor, otherwise known as the Foveon sensor, is currently underway. That development process can be broken down, roughly, into three stages:
Stage 1: Repeated design simulations of the new three-layer structure to confirm that it will function as intended. Stage 2: Prototype evaluation using a small image sensor with the same pixel size as the product specifications but with a reduced total pixel count to verify the performance characteristics of the image sensor in practice. Stage 3: Final prototype evaluation using a full-frame image sensor with the same specifications as the mass products including the AD converter etc. Sigma confirms that it has completed the design simulations of the Foveon sensor and that it should function as intended. The company is currently in Stage 2, where it is prototyping the design on a much smaller sensor than the full-frame sensor that it hopes to make available in a finished camera. Yamaki says that based on the evaluation results of that prototyped smaller sensor, Sigma can decide whether to proceed to Stage 3 or go back and re-prototype Stage 2. This explanation seems to indicate that Sigma does not have to go all the way back to the basic design phase if something does not go as planned in Stage 2. “When we proceed to Stage 3, we will verify the mass-producibility of the sensor with research institutes and manufacturing vendors based on the evaluation results, and then make a final decision on whether or not to mass-produce the image sensor,” Yamaki writes. “Although we have not yet reached the stage where we can announce a specific schedule for the mass production of the image sensor, we are determined to do our best to realize a camera that will truly please our customers who are waiting for it, as soon as possible.”
Troubles with the Foveon Sensor
Sigma’s Foveon sensors use a proprietary three-layer structure in which red, green, and blue pixels each have their own full layer. In traditional sensors, the three pixels share a single layer in a mosaic arrangement and the camera “fills in” missing colors by examining neighboring pixels. Since each pixel of a photo is recorded in three colors, the resulting photo should be sharper with better color accuracy and fewer artifacts. Unfortunately, the development of the full-frame Foveon hasn’t been going smoothly. The company has been working on it since 2018 , but in early 2020 indefinitely delayed the sensor . A year later, the company announced that it was forced to scrap all efforts it had made to that point and start from scratch . Sigma at least appears closer to making the full-frame Foveon a reality, but is still clearly a ways off yet.

Sigma is in the Second Stage of Prototyping a New Foveon Sensor

Aug 04, 2021
A lot of words have been written and exchanged about the difference between — and possible advantages or disadvantages of — CCD (charged-couple device) and CMOS (metal oxide semiconductor + active-pixel sensor) camera sensors. What really is the difference between them? It is a debate that has existed since CMOS first began its journey toward being the industry dominant technology for camera sensors. This happened gradually throughout the 2000s and by the middle and particularly the end of that decade, it was clear what would win out for both stills and video. What we will attempt to do is add a bit of clarity to this issue by covering the scientific differences — in language that has hopefully been distilled down to be accessible and concise yet also informative and detailed — as well as addressing some of the most common subjective talking points which have floated around the internet for the better part of two decades. Editorial Credit: atdigit / Shutterstock.com
It’s important to note that we are limiting this discussion to non-scientific (non-specialty astro, medical, etc.) and non-video sensors. In other words, we are talking about CCD and CMOS sensor tech in stills cameras for the sake of brevity. An expanded conversation that goes into the tech across multiple disciplines would be the length of a book. Bear in mind then that some of the statements below do not hold true for applications outside the still photography space. A Bit of History
To simplify things, let us start in the early to mid-2000s, by which time digital photography had established itself as a worthy alternative to film for many professionals. Both CCD and CMOS technology existed well before that point, but we want to keep things somewhat brass tacks here. In the very late 90s and early to mid-2000s, the camera industry was in upheaval in quite a few ways. Companies were competing for dominance as they juggled the analog to digital transition and digital sensor technology was all over the place. What is germane to this topic is that we saw a variety of different and unique sensor technologies being used across the different manufacturers, fluctuating and evolving frequently. Today we have essentially four types of sensors: CMOS with a Bayer CFA, CMOS without a CFA (monochrome sensors), CMOS with Fujifilm’s X-Trans CFA, and Foveon sensors. As you may be able to guess, that really means we have just two types of actual sensor technology: CMOS and Foveon. While there were unique sensors here and there (like the Nikon JFET-LBCAST ), most cameras produced in the early to mid-2000s were fitted with CCD sensors. This gradually began to shift over the course of the decade. Undoubtedly, that was driven by the market leader, Canon, who implemented the first full-frame CMOS sensor with the Canon 1Ds in 2002 and continued to use CMOS technology in a majority of its cameras moving forward. The debut of the Nikon D3 and Sony a700 in mid-2007 firmly cemented CMOS as the dominant technology for photographic cameras — not surprisingly, it was this same year that CMOS sales surpassed CCD sales. The only exception was the medium format arena, which would continue using CCD sensors until the release of the Hasselblad H5D-50c in 2014. Camera technology tends to trickle upward, after all. Naturally, the big question is “why?” Why did companies abandon CCD in favor of CMOS? Objective Differences: The Science
Sensors themselves are completely monochromatic. In other words, they measure light — it isn’t until a color filter array (CFA) is installed over the sensor that they can capture color information. This is usually done with an RGB Bayer mosaic, whether the sensor itself is CCD or CMOS. Both types of sensors are built with arrays of silicon photosites, also known as pixels. In digital cameras, there will be millions of these pixels — one million pixels is better known as a “megapixel.” These pixels are oriented in a pattern of rows and columns, ultimately coming together to form the rectangular shape we know as a sensor. When light passes through a lens and strikes these silicon pixels, photons from the light interact with atoms in the silicon substrate. As this happens, electrons get kicked in higher energy states and are sent moving through the structure. That is the nuts and bolts of a basic sensor, whether it’s CCD or CMOS. After this point, the way in which each of them turns these photons into a digital image reveals their differences — this process is otherwise known as “reading the sensor” or a “readout” and is when the translation of physical electric activity into digital data occurs. CCD
In a CCD sensor, each pixel contains a potential well which is often likened to a bucket. During the exposure, as light strikes the sensor, this potential well collects photons, and the photons liberate electrons. The electrons amass during exposure, constrained within the “bucket” by electrodes and vertical clocks. After exposure, electrons migrate down each row of the CCD, and the charge is gathered from each pixel along the way. Eventually, they reach a “container” at the end of the row known as an amplifier. This amplifier measures the number of photons that were loose in each well and converts that into a voltage. The process continues from there onto the gain stage and then to the ADC (analog to digital converter). With most photographic CCD sensors, a mechanical shutter is necessary to avoid potential “smear” — since the sensor is read out one line at a time, any light that falls on photosites during the process can create vertical smear-type artifacts. This obviously precludes CCD sensors from being used with live-view. As a reminder, we are specifically referring to photographic stills cameras — CCD cinema cameras use a different design. Editorial Credit: gritsalak karalak / Shutterstock.com
You may at this point say, “hey, early compact digital cameras with CCD sensors had live view!”
Yes and no. These cameras did not have a true live view as we know it today. Instead, they displayed considerable lag, particularly noticeable when the camera is moved. You might chalk this up to the slow technology of the time, but it was really a limitation of the slow readout speed of the CCD chips — each frame had to be binned and transferred to the LCD screen or EVF, which could take up to a second or more. So, you end with a quasi-live image with an abysmal framerate, though it’s decent enough for framing static or mostly static subjects. CMOS
Jumping over to CMOS sensors, everything above remains true as far as pixels collecting light (photons), however, the two technologies diverge at the readout stage: every individual pixel in a CMOS sensor has its own readout circuit — a photodiode-amplifier pair that converts the photons into voltage. From there, each column of the CMOS sensor has its own ADC. One upshot of this is significantly lower production costs to produce CMOS sensors since both the ADCs and imaging sensor are on the same silicon die. It also allows for a more compact design, which is particularly beneficial for smartphones and very compact cameras. Editorial Credit: gritsalak karalak / Shutterstock.com
As you would expect, since each pixel is read out in parallel, CMOS sensors can be much faster. Today, this is particularly important for both video and the use of silent electronic shutters — faster sensor readout means less distortion of moving objects (“rolling shutter”) as well as the potential for uninterrupted live-view. Cameras like the Canon R5 and R6 and Sony Alpha 1 can read out the sensor fast enough that even high-speed objects like race cars or athletes in motion do not warp or distort when using the electronic shutter. It also aids in the use of flash, as seen in the Sony Alpha 1 which can flash sync with the e-shutter at the same speed as many mechanical shutters. None of this would be remotely possible in a CCD sensor. CMOS sensors also require less power and produce less heat. This is one reason that global shutter CCD (“frame transfer CCD”) cameras found in some digital cinema cameras could not be implemented in stills cameras — while the large body and hefty batteries of the cinema camera mitigated the heat and power issues, this was not possible in a significantly smaller package. Via Creative Commons
Sony’s introduction of BSI (backside illumination) technology in 2009 in its Exmor R CMOS sensor further entrenched the dominance of CMOS technology. Traditional (front side illuminated) sensors have their active matrix and wiring on the front surface of the imaging sensor. Detrimentally, this reflects some of the incoming light, which reduces the amount of captured light. BSI moves this matrix behind the photodiodes, allowing for an approximate half-stop (50%) increase in the amount of collected light. BSI allowed CMOS technology to pull even further ahead of CCD. So What is it Good For? CCD did have its advantages over CMOS, though most of them have been solved in the years since CMOS took over. Take the Nikon D1 from 1999: it sports an APS-C CCD sensor and delivers 2.7-megapixel images — however, the sensor itself has 10.8 million photosites (i.e., 10.8 megapixels). Because of the serial readout of the pixels, it is very simple to implement on-sensor pixel binning to combine charges from neighboring pixels in a CCD design — this results in higher sensitivity and a greater signal-to-noise ratio. While you can pixel bin with a CMOS sensor, it must happen off-sensor and you can’t combine charges from neighboring photosites. Sigma’s Foveon sensors were developed partially to combat this problem. A good example of this in a slightly more modern camera is 2008’s Sony F35 CineAlta camera. It contained a single Super 35 (roughly the size of APS-C) CCD chip with a resolution of 12.4 megapixels. However, it only produced a 1920×1080 (HD) file. This is the result of on-chip pixel binning and it allowed, among other things, the camera to output true RGB 4:4:4 data — no interpolation necessary. It is possible to do this with CMOS technology, but it has to happen off-chip. For example, it is possible to downsample a high-resolution 4:2:0 video file to a lower resolution 4:4:4 file in software. Furthermore, many stills cameras with in-body image stabilization (IBIS) offer pixel shift, which can be used to generate a high-resolution file or a true color file of native resolution. But these are not ideal alternatives to on-chip binning. CCD sensors also have a non-linearity that is often (though not always) lacking in the more linear CMOS sensors. This means pleasing and more natural roll-off in the quartertones and highlights — however, this exists at the expense of a higher noise floor, which is particularly noticeable in the shadows, even at base ISO. It also requires careful and precise exposure due to the unforgiving latitude of CCD sensors, but when done properly, it results in what many consider to be more film-like image quality. Film, after all, is also extremely non-linear with exceptional highlight latitude but little tolerance for pushing the shadows without aggressive pattern noise or color shifts. Subjective Differences: The CCD vs. CMOS Debate
This is the area where things get complicated, but it’s also the root issue at the heart of the CCD vs CMOS debates across the depths of Internet forums. On one side are those who feel that CCD sensor cameras produce superior images. On the other side are those who tout the many benefits of CMOS technology, with some arguing that there isn’t much difference in the image output between the two. From my perspective, there are certainly merits to the argument that CCD sensors can and do produce more pleasing files — but of course, the entire concept of “pleasing” is a subjective one. A lot of it is related to the aforementioned tonal curves inherent to each sensor type. Non-linearity produces files that more closely mimic human vision — it is incredibly common for our vision to clip totally to black, but we almost never see completely blown highlights. Hypothetically, if we could see twenty stops of dynamic range, the spread might look something like 12 stops over and 8 stops under middle grey. Contrast that to a hypothetical 20-stop CMOS sensor, which would likely be the exact opposite. As an aside, this is one reason the Arri Alexa is so popular for cinema and considered the most “film-like” — at its base ISO of 800 it allocates more dynamic range above middle grey than below, something which is not found in almost any other cinema camera. Unusually for a digital camera — stills or cinema — the Arri Alexa’s ALEV III sensor’s native ISO 800 displays highlight bias. Some argue CCD sensors produce more natural and accurate colors. Their color output is undoubtedly different, and I think there is some merit to the idea of color accuracy, at least based on my experience with many CCD cameras. Some speculate this has to do with the CFA designs and perhaps it does — certainly with some cameras like Fujifilm’s SuperCCD cameras this is the case. But we also see extremely accurate and neutral colors in many CMOS sensors — Hasselblad is the king of neutral color, in my opinion. Numerous blind tests have also shown that photos from CMOS sensors can easily be matched to images from a CCD (and vice versa) at least as far as color goes. From my perspective and experience, CCD output in optimal conditions (good directional light, low ISO, punchy colors) will result in deeper blues, surprisingly accurate reds, warm midtones, neutral and cool shadows, and very pleasing tonal transitions from the quartertones into the highlights — if those highlights aren’t clipped. If a scene is going to have clipped highlights, then results will favor the CMOS because the roll-off avoids some of the harsher, sharp edges you find in clipped CCD highlights. Almost all of these things, given each that image is properly exposed, can be matched relatively easily with some judicious use of HSL (hue, saturation, luminance) sliders. What Does it All Mean? So, is there a difference between CCD and CMOS images? Absolutely, there is no doubt — both in design and output. Are those differences important? That depends. If you are a fan of using straight out of camera files, then you’ll likely find the output of CCD sensors to be more pleasing — images are punchier, more colorful, and can work very well without much adjustment. Then again, the same is true of many CMOS-based cameras with excellent, adjustable JPEG engines — Fujifilm and Olympus are the most notable, though far from the only examples. Editorial Use: Yury Zap / Shutterstock.com
But if you shoot and process RAW? Not only can you mimic the output of CCD in that case, but the wider latitude of CMOS allows you a much greater range of options. There is one thing is that is without doubt: CMOS technology has outgrown and outpaced CCD, at least for stills and video imaging. But perhaps you love the output from your Leica M9 and don’t need live-view, silent electronic shutter, wide dynamic range, or exceedingly impressive low-light capabilities. In that case, cherish and use your M9. But if your camera is worse for wear and needs an upgrade, there’s no reason to fret over what sensor is in your replacement. Image credits: Header image graphic made from Creative Commons elements and those licensed via Depositphotos .

What is the Difference Between a CCD and CMOS Camera Sensor?

(Image credit: Nokishita)
A new leak has revealed the first images of the incoming Sigma FP L – and they suggest it'll be another intriguing, modular full-frame camera with a new sensor and some unique accessories. The original Sigma FP became the world's smallest full-frame camera when it launched in July 2019, partly thanks to the fact that it completely ditched the mechanical shutter, instead relying solely on its electronic shutter. The result was a camera that was very much designed for roaming filmmakers and cinematographers – and it appears the Sigma FP L will follow this trend, only with a new sensor and some unusual accessories. These are the best full-frame cameras you can buy right now
Or check out our guide to the world's best mirrorless cameras
The Sigma FP L was expected to launch at the CP+ 2021 show in February, but it sadly didn't arrive, with Sigma instead focusing on its new 28-70mm F2.8 DG DN lens. According to the latest rumors , though, the camera will now be launched at a Sigma Stage Online event on March 23. So what can we expect from the compact mirrorless camera? Earlier rumors suggested the Sigma FP L might have a new 60MP Foveon sensor. Foveon is a unique sensor technology that's been around for almost 20 years, but has never become as popular as the dominant Bayer-filtered sensor design used by most other cameras. Foveon's special trick is that it interprets color by capturing light at three different depths in the same photosite, rather than the Bayer approach of using a grid of red, green and blue filters. While Foveon isn't perfect, this means it doesn't need to do any demosaicing (the process of reconstructing an image from a Bayer pattern), which can help it produce lovely colors and detail. Sadly, Sigma recently confirmed that its 60MP Foveon sensor won't be ready this year and is still in development, so the Sigma FP L won't have this sensor. This makes it a slightly less interesting cult camera, but some leaked accessories suggest it will still bring some interesting modular ideas. (Image credit: Nokishita)
Full throttle
The Sigma FP L is still expected to be a full-frame camera like the existing FP, with L Rumors suggesting it will have a new Sony chip with a 60.75MP resolution. This will apparently have a 30MP mode with "the same quality you'd expect from a Foveon X3 sensor". We'll have to wait until its rumored announcement next week for more details on that, but one thing we do have (thanks to the ever-reliable Nokishita ) are some leaked images of some of its new accessories. First up, there's an intriguing side-mounted viewfinder called the EVF-11. Like the Sigma FP, the FP L doesn't appear to have a built-in viewfinder, so optional EVFs are an essential accessory. This is a slightly unusual design, though, with most add-on EVFs designed to instead sit on top of the camera rather than to the side. The EVF-11 has a rumored price of 75,000 yen without tax (around $690 / £495 / AU$890). With other accessories like two new eyecups and a hard case also rumored to be en route, it appears the Sigma FP L will really double down on that modular design that makes it such a versatile little full-frame camera. We're very much looking forward to hearing more about it next week.

Sigma FP L leak suggests it'll be a unique modular full-frame camera

Teradyne supplies automation equipment for test and industrial applications. Teradyne Automatic Test Equipment (ATE) is used to test semiconductors, wireless products, data storage and complex electronic systems, which serve consumer, communications, industrial and government customers. Its industrial automation products include collaborative robots, autonomous mobile robots and sensing and simulation software, used by global manufacturing and industrial customers. The company was founded in 1960 and is based in North Reading, Massachusetts.

Teradyne

announced Foveon Inc. , of Santa Clara , CA , has selected the Teradyne test system for CMOS Image Sensor device test .

Foveon selects Teradyne IP750 - News Search on EMSNow

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