#cmossensor

I'm looking for a CMOS camera sensor for a FOSH project. I'm just looking for a surface mount chip without the lens.

It looks like two big brands are onsemi and omnivision. I've applied for NDA access to the datasheets, but I'm wondering if there are good options with open specs? How do people generally release FOSH based on chips with NDA specs?

I've gotten the OV7670 prototype boards configured using I2C and I can read frames out using the parallel interface.

Parallel interfaces are easy. Many cameras now have MIPI interfaces. Is it easy to read MIPI data? I am planning to use an FPGA to read the camera data, so although parallel would be easiest, I imagine there could be a MIPI Vertilog 2005 implementation that I could compile to run in my FPGA?

#foss #fosh #camera #sensor #camerasensor #fpga #mipi #onsemi #omnivision #cmossensor

Cmxelcs Chengsuchuangcmxelcs
2025-05-10

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petapixel (unofficial)petapixel@ծմակուտ.հայ
2021-09-15

A Closer Look: How I Created a 248MP Photo of the Sun

A big ball of light hovers above our heads everyday. It is always there and most people take very little time to notice it. While we are not suggesting that you spend time staring at it and going blind in the process, science has allowed us the ability to look directly at the sun in the safest ways.

As consumer technology has become more affordable, the average person can peer into the multiple layers of the sun using dedicated equipment that can be purchased at any good telescope retailer.

In this article, we will be focusing specifically on a layer known as the Chromosphere: an area of the sun that is visible within the orange to red spectrum. Using a specialized filter, this device blocks out all unwanted light while passing the specific bandpass we are looking at.

This full-disc image of our sun is created using a large refracting telescope and a high-speed CMOS monochrome camera.

A special type of filter known as an etalon is used in conjunction with a blocking filter. Since the layer of the sun is what we want to observe, the blocking filter is designed to let in light at 656nm wavelength. In this case, a Daystar Gemini is used which also has a 4.2x telecentric Barlow built-in.

The camera in question is made by QHYCCD, a company that specializes in making cameras for the astrophotography market. This particular camera, the QHY5III-174M has a smaller sensor compared to what we are used to. At only 2.35-megapixels, a final image is built of 90 panels to create a mosaic of sorts, making a complete image of our star.

Each panel or image is made up of a high-speed video capture of 1000 frames, which is later stacked together to create a highly detailed image with smoother gradients and less noise.

Since the camera has such a small sensor, a tracking mount was used with the assistance of a controller to pan across the sun, taking captures at various steps. Since the sun is actually in constant motion, the time taken to capture each panel has to be under a certain time frame. This sequence took approximately 25 minutes to complete to ensure that the surface did not change too much when creating the final image.

Astrophotographers often employ a technique during the initial phase to sort out what is signal and what is noise. The basic idea is that an image with a lot of noise when combined with other images from the same framing, will result in a better image.

Once these images have been stacked, a process is then applied which helps sharpen the image. Using a specific technique known as deconvolution, a software called IMPPG allows details to be pulled back in. This is much like the pre-programmed settings found in almost all DSLR and mirrorless cameras. Astronomy cameras have these pre-processing steps removed to allow the user more control over the image at the cost of time spent processing.

Next is the long task of aligning each image. While there are many software options to make this process faster or automated, images such as these do not always line up correctly. Often, two images do not contain any specific features for the software to create alignment points and fail at creating stitched images without some type of distortion or misalignment.

After each frame has been individually aligned, the images are then blended together to make a seamless image. Photoshop Auto-Blend is able to handle this particular task extremely well, even if the two adjacent frames have different varying levels.

Once each panel had been aligned and blended, a few other tricks were also used to enhance the details further. Applying HDR Toning, details begin to pop out. The HDR image is blended together with the previous result, to make a smoother transition. Varying hotspots and dark patches are also removed to create a more uniform image using the Camera Raw functions within Photoshop.

Processed Mono Invert Processed False Mono Positive

Once the final image is achieved, a false-color is applied to the image. Since our sun is not actually yellow, a curves adjustment is used to give the coloration that most people would associate with the sun during sunset.

Processed False Color Positive

The final image created is a giant 248-megapixel image that freezes the sun at that moment of capture, never to be seen again in the exact same way.

While a smaller telescope can be used to create these images, larger telescopes have the added benefit of being able to get more details than would with a smaller counterpart. At 1200mm focal length, plus the added 4.2x magnification, the smallest minor details become monstrously big. Each feature can be the size of the Earth and the larger ones would swallow Jupiter whole several times over.

About the author: Simon Tang is an accomplished astrophotographer whose work has been widely recognized, including by the Royal Observatory in its Astronomy Photographer of the Year competition (under the name Siu Fone Tang). Tang regularly shares his astrophotography images on his Instagram.

#editorial #inspiration #walkthroughs #248megapixel #astrophotography #cmossensor #editing #falsecolor #howto #monochromecamera #qhyccd #simontang #sol #solar #star #sun

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petapixel (unofficial)petapixel@ծմակուտ.հայ
2021-09-10

Why Camera Sensors Matter and How They Keep Improving

What is the most important aspect of a camera to consider when looking to buy a new one? In this video, Engadget put camera sensors in the spotlight and reviewed how they have improved and what role they play in today's photographic equipment.

Camera brands regularly release new cameras, with each model improving on its past versions. However, video producer Chris Schodt from Engadgetpoints out in the company's latest YouTube video that it may appear camera sensors haven't progressed as rapidly in the recent past, although resolution has increased. This is because modern-day cameras -- such as the Canon EOS 5D released in 2005 -- were already able to produce high-quality images over a decade ago and still continue to do so.

Camera sensors, in technical terms, can be described as a grid of photodiodes which act as a one-way valve for electrons. In CMOS sensors -- which are widely used in digital cameras that photographers use today -- each pixel has additional circuitry built into it aside from the photodiode.

These on-pixel electronics help CMOS sensors quick speed because they can read and reset quickly, although, in the past, this characteristic could also contribute to bringing up fixed-pattern noise. However, with the improvement of manufacturing processes, this side-effect has been largely eliminated in modern cameras.

Schodt explains that noise control is crucial to a camera's low light performance and dynamic range, which is a measure of the range of light captured in the image between the maximum and minimum values. In a photograph, those are between white -- such as when pixel clips or is overexposed -- and black, respectively.

Clipped or overexposed pixels in an image

In an ideal scenario, camera sensors would capture light, which is emitted as photons, in a uniform way to reconstruct a perfectly clear image. However, that isn't the case because they hit the sensor randomly.

One way to deal with this is to produce larger sensors and larger pixels, however, that comes with a large production cost and an equally large camera body, such as the Hasselblad H6D-100c digital back which has a 100MP CMOS sensor and a $26,500 price.

Other solutions include the development of Backside Illuminated sensors (BSI), such as the one announced by Nikon in 2017 and Sony first in 2015. This type of sensor leads to improved low-light performance and speed. Similarly, so does a stacked CMOS sensor that provides even faster speeds, such as the Sony Micro Four Thirds sensor published earlier in 2021.

Smartphones, on the other hand, use multiple images and average them together to improve noise and dynamic range, like the Google HDR+ with Bracketing Technology, which is also a direction that several modern video cameras have taken, too.

Looking towards the future of sensor development, Schodt explains that silicon, which is the material currently used to make sensors, is likely to stay, although some alternative materials have been used like gallium arsenide and graphene. Another possible direction is curved sensors, although they would make it difficult for users as curved sensors would need to be paired with precisely manufactured lenses. In practical terms, photographers would have to buy into a particular system with no option of using a third-party lens.

It's likely that in the future focus will be on computational photography. Faster sensors and more on-camera processing to make use of smartphone-style image stacking might make its way to dedicated cameras, for example, in addition to AI-advanced image processing.

In the video above, Schodt explains more in detail the technical build of sensors and how their characteristics correlate to the resulting images. More Engadget educational videos can be found on the company's YouTube page.

Image credits: Photos of camera sensors licensed via Depositphotos.

#educational #technology #backsideilluminated #bsi #camerasensor #cmos #cmossensor #curvedsensor #digitalbacks #engadget #sensor #smartphonecamerasensor

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petapixel (unofficial)petapixel@ծմակուտ.հայ
2021-08-04

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

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.

Credit:Cburnett, CC BY-SA 3.0, via Wikimedia Commons

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.

#educational #equipment #guides #technology #arri #arrialexa #bayer #canon #ccd #ccdsensor #cmos #cmosimagesensors #cmossensor #explained #explainer #foveon #hasselblad #leica #nikon #pixels #sensor #sigma #sony

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