Size and Capture + ISO Invariance

Last Update: 27th June 2025

Introduction

This article reviews the "size and capture" theory, ISO invariance, and insights from my series on the extended ISO range of Olympus cameras. This is not an academic paper exploring ISO invariance or the "size and capture" theory, as these are commercial programs designed to promote FF cameras. As you go through this article, consider why manufacturers deem it necessary to apply sales arguments supported by the "size and capture" theory or promotional campaigns relying on astroturfing.

Also, study these articles:

• Exposure techniques versus sensor size - link
• ISO Low, L100, L64, and Flash Photography - Part 2
• See this discussion I had with AI on sensor size - link

The above video compares the Fuji GFX100S to the Sony A6000. While the Fuji has an MF sensor and the Sony a crop sensor, Fuji's pixel area is only 5% larger. The same Sony sensor is larger than the EM1 III sensor, and its pixel area is only 15% larger. Acknowledging optical differences between sensor sizes, such as blurring the background, we know image sensors also have technical limitations. For instance, image sensors only saturate when fully exposed, and each sensor produces noise (SNR) as a result of the sensor's so-called noise floor. I thought the video was entertaining, informative, and a welcome change to the almost daily "size and capture" or "bigger is better" promotions.

All photographers should know the above illustration...

Why do all digital cameras have noise? Each image sensor has a noise floor, which equals the sum of shot and read noise. The conversion of photons to electrons and the electronic components in the control circuits of the pixels also add noise to the sensor's noise floor. Does this mean we could see more noise from 61MP versus 20MP image sensors? Figure 3a illustrates the image sensor's photons-to-electrons conversion characteristics and the active noise components in the sensor.

All digital cameras have technical limitations, such as too little dynamic range, rolling shutter (sensor readout speed), and noise. Acknowledging these limitations, the Olympus engineering team created innovative features such as Auto HDR, stacking options, composite, and computational features like the high-resolution mode, Live ND filters, creative modes, and finally the new digital M43 sensor format. One of the most exciting Olympus developments is the TruePic image processor.

Medium-format and full-frame photographers also experience technical and optical limitations. For example, crop sensor cameras have a larger depth of field (DOF), whereas MF and FF cameras have a shallower DOF. That's why landscape photographers like Gavin Hardcastle prefer to use focus stacking and exposure bracketing. See how Gavin manages his landscape scenes in this video.

Why would marketers use undisclosed promotions?

Undisclosed promotions are commercial actions aimed at social media and mainstream outlets. It uses trusted personalities to add a commercial spin to product information while promoting it as factually correct to an unsuspecting audience. It relies on the influence trusted authorities enjoy without disclosing that it's part of paid promotions. A better way would be for the audience to know they are viewing a sponsored promotion. Which approach would you prefer?

The "size and capture" theory, better known as "bigger is better," likely originated from one of the following scenarios. One such scenario focuses on the diagonal measurement of the image sensor (see Fig. 4). This clarifies why an M43 sensor is proportionately half the size of a full-frame sensor.

See this article for comparisons and more information.

Another such scenario is marketers focusing only on one IQ variable. It seems like they took pixel area and repurposed it as pixel pitch in an effort to link pixel area to sensor size. Undisclosed promotions pushing "size and capture" statements started in 2012. ISO invariance followed years later. The original E-M5 is one of only a few M43 cameras that received credible reviews and critique. Those distrusting the "size and capture" theory also experienced the transition from objective to undisclosed fact statements as the preferred marketing vehicle for "sensitive" corporate programs.

2012 was the year in which Olympus introduced its 2nd generation of mirrorless cameras with 5-axis IBIS for stills and video. The EM-5 MKI revolutionized the mirrorless segment. In stark contrast, Canon and Nikon continued to design digital single-lens reflex (DSLR) cameras as they believed the 60D, 5D3, D800, and D5200 were future-proof. They only introduced FF mirrorless cameras in 2018.

How does the engineering community view the world?

Design engineers review each aspect of a camera, whereas marketers deliberately focus on sensor size and pixel pitch. Engineers consider effective pixel area, lens image circle, image processor, general energy needs, the camera's physical size (temperature & cooling), IBIS (size and weight efficiency ratio), and the size and weight of the camera/lens combination. In other words, the engineering community carefully considers the technical and optical limitations of each camera solution.

What distinguishes effective pixel area from conventional pixel area? The pixel wiring of standard CMOS sensors is placed above the pixel's light-sensitive area. This diminishes the effective pixel area, thereby affecting the sensor's efficiency in capturing reflected light. In contrast, BSI (backside illumination) and Live MOS sensors represent wiring enhancements over standard CMOS technology. BSI sensors achieve an effective pixel area exceeding 98%, while Live MOS sensors hover around 87%. In comparison, standard CMOS sensors have an effective pixel area of less than 70%.

See the video below for more about sensor types.

Spend a few moments to review the following:

• Olympus improved the ISO performance of the EM1 II with a 3rd stop (4%). How?
• Why do we never see discussions on the Live MOS sensor, and those who ask are...
• Pixel pitch defines the resolution/quality of TV displays. Why apply that to sensors..?
• How could it be that 2 cameras with the same sensor size and resolution are different?
• Sony users can reconfigure the Sony A7 series to APC mode. What happens to the IQ?
• Photographers typically see only small changes when "upgrading" to FF cameras. Why?
• Up to 98% of all camera reviews repeat the same "size and capture" phrases/keywords.
• Why did reviewers start to include ISO Invariance in more recent camera reviews?
• Have you seen any manufacturer actively promoting ISO Invariance? Why NOT?
• Which information is repeated most in reviews? Sensor size or Sensor Sensitivity?

The "size and capture" theory cannot explain the shadow noise in the above image (taken with the Sony A7RIV).

Did 12 years of undisclosed promotions add any value to photography?

Start by counting the times you find sensor-size "phrases or statements" on forums and in reviews. You will find that paid promoters link almost anything to sensor size. For example, how often do forum posters (astroturfers) review the benefits of having a saturated sensor with a higher SNR?

Why keywords? A well-known speaker said people accept anything if the story is big and repeated enough. This is why the mainstream media repeat "big" stories (keywords) for days. Like "size and capture," people learn to trust anything that is presented as fact and repeated enough.

"Size and capture" keywords are literally repeated like a BIG news story:-

• The BIGGER one captures more light
• The BIGGER one has more image quality
• The BIGGER one produces less image noise
• The BIGGER one improves your dynamic range
• The BIGGER one offers better subject separation
• The BIGGER one has more... really, is there NO end..?

How often do we see discussions about the optical and technical differences of digital cameras? Why do marketers lump everything into one basket while promoting the bigger is better story?

Undisclosed promotions offer nothing new. The biggest concern with undisclosed marketing is the high level of dishonesty. The dishonesty is obvious in the "size and capture" theory and ISO invariance. I am always stunned at people accepting almost anything from the same marketing techniques.

Why is this important? Oversimplification limits the photographer's capacity to fully grasp and apply their cameras. For example, did you know that we can effectively control the camera's visible image noise (SNR)? Simply purchasing a new camera with a larger sensor is not necessarily a solution.

The above illustration illustrates 2 scenarios. "Size and capture" followers and those providing theoretical information.

Let's consider some basic technical aspects.

Theoretical information is associated with camera or sensor manufacturers and academic institutions focusing on mathematics and Newton's law of gravity. How did Olympus invest its R&D budget? They focused on more efficient sensor technologies, such as Live MOS and back-illuminated (BSI) sensors, alongside enhancements such as stacked BSI sensors, efficiency, and sensitivity (quantum and optical efficiencies). Olympus R&D engineers were masters at harmonizing photography solutions consisting of sensor technology, image processing, editing software, and high-quality lenses. 

It's interesting to study manufacturers. For instance, the trend is BSI sensors with more megapixels, and one of the more intriguing areas of R&D is the physical design of the pixel (XT-5). Another critical aspect of sensor design is firmware replacing control wiring. The result is sensors with less control wiring and a smaller noise floor. For example, sensor manufacturers use "lens elements" over the pixels to improve the pixel's optical efficiency or firmware to reduce the image noise associated with more pixels. Olympus used firmware to boost the EM1 II's noise performance by +1/3 EV.

Why didn't Olympus cameras go beyond 20MP? The reasons are clear when we consider efficiencies and pixel area. More pixels mean more control wiring and smaller pixel areas. This typically adds more noise to the sensor's noise floor and lowers optical efficiency. Instead of simply adding more pixels, Olympus opted for sensors with higher efficiencies, enhanced TruePic processors, and the quality improvements that come from advancing their 16MP to 20MP sensor technologies. This choice accounts for the enhanced image quality seen in the E-M1 III, OM-1, and OM-3 models. Other factors to consider include file sizes, computer configurations, image editing, and the ideal resolution for various kinds of photographers, whether they are casual, hobbyist, or professional.

Why did marketers introduce pixel pitch? Why use a term associated with TVs or LED displays? The term pixel pitch deliberately shifts the focus from pixel area to size. For example, pixels capture photons, and larger pixel areas mean the sensor is optically more efficient (sensor sensitivity).

Marketers deliberately confuse digital photographers when referring to stacked CMOS sensors. Sony did an excellent job of introducing and promoting BSI sensors with larger effective pixel areas. In an effort to extend the Standard CMOS sensor's life cycle, marketers use counterarguments (phrases) such as "stacked CMOS" or CMOS sensor when referring to Olympus BSI or Live MOS sensors. Which manufacturer has the highest number of standard CMOS camera models in 2025?

Why would manufacturers use standard CMOS sensors in 2025? Why use the basic CMOS platform if the Live MOS and BSI variants are more efficient? Each variant offers advantages and disadvantages. While the trend is BSI, some manufacturers might prefer standard CMOS sensors for profitability and reliability reasons. The real question is, how much of an IQ difference do BSI sensors make?

How much of a difference does any of the above make? Study this article.

Unlike undisclosed promoters, manufacturers understand the importance of sensor sensitivity.

One clearly recognizes the main message in the above description, especially if you value accurate information. The GH5S achieved the highest-ever M43 sensitivity with 50% fewer pixels, and Dual ISO made it possible to more effectively manage/control the visibility of the sensor's noise floor. 

Always remind yourself that the size of the sensor stayed the same while the pixel count went up by as much as 400% over the past 20 years. Have you ever wondered how much your IQ suffered with 400% smaller pixel areas? How did sensor manufacturers cope with the losses of these smaller pixel areas or the increased noise floor resulting from more control wiring?

Why did marketers thought it's necessary to invent ISO Invariance?

Similar to "size and capture," ISO invariance is a commercial concept that lacks theoretical support. It's only referenced in "independent" articles, camera reviews, and social media. If this concept were to be theoretically correct, ISO invariance would suggest that researchers have found a way to successfully replace the sensor's control wiring with superconductors, effectively eliminating any read noise or resistance to electrical current. Some claim that modern sensors have no read noise.

The Photons to Electrons graph in Figure 3a is part of the European Standard for Image Sensors. The Photons to Electrons graph is also discussed in this article. The main points are:

• Each image sensor comes with a native noise floor
• The noise floor has shot, read, and Temporal noise
• AST is the sensor's Absolute Sensitivity Threshold
• The image sensor will saturate when fully exposed
• Sensor saturation and SNR are critical IQ elements
• Guess what? Promoters reject this information...

Figure 3. The above illustration gives more accurate reasons why image sensors are different.

What factors cause noise floor variations between sensors? The primary elements determining image sensor sensitivity is quantum efficiency, optical efficiency, type of sensor, and pixel design. Additionally, factors such as sensor architecture, image processing algorithms, firmware, and wiring can affect temporal noise. It is important to note that researchers do not overlook other sources of noise, including elevated sensor temperatures, shot noise, read noise, and quantization. It is a common misconception that larger sensors inherently produce lower noise levels.

Figure 3a

Why do reviewers and forum experts ignore the sensor's noise floor when claiming large sensors are better? ISO Invariance is the promoter's version of addressing the sensor's Noise Floor.

Promoters like to suggest ISO-invariant sensors have more dynamic range. The reason for having more dynamic range is linked to the design of the sensor and the absolute sensitivity threshold (AST). See the above illustration. Marketers will alter any information to push a commercial narrative.

It's impossible to claim that large sensors receive more light, have no read noise, and agree that all sensors have a noise floor. How does one explain the phenomena of sensor saturation and signal-to-noise ratio (SNR) if photographers are led to believe that sensor size is the one and only image quality variable? ISO invariance replaced the theoretical understanding that all image sensors have a noise floor and/or technical limitations. In essence, ISO-invariant sensors supposedly have no noise floor, because ISO-invariant sensors are only affected by shot noise (dust particles). Why is this an unlikely scenario? Misinformation is confusing and invariably leads to further inaccuracies.

The Canon M5 (80D) is another ISO Invariant camera - my experience with Canon CMOS sensors is much shadow NOISE.

Why would they say larger sensors receive more light?

One of the more frequently used forum statements suggests that it's physics. That means we should simply accept the "science or physics." You don't need more information to accept that larger sensors receive more light. Let's have a quick look at how they visualize this "more light" concept.

Figure 4

What does it mean when forum promoters say it's all about physics? Modern marketers and social media (forum) promoters focus on visual aspects and not theoretical information. Crop sensors and the crop sensor image circle are visually smaller than those of full-frame sensors. Instead of saying different sensor sizes receive the same image data from equivalent field of views (FOV) or focal lengths, they prefer photographers to think larger sensors capture more light. In other words, visually larger sensors have a "bigger" image circle, which "proves" they receive more light.

What is the "Size and Capture" theory?

The "size and capture" theory posits that both the dimensions and type of a sensor play a crucial role in determining image quality. Social media experts frequently claim that larger sensors improve light-gathering capabilities, enhance overall image quality, provide superior color fidelity, minimize noise, and broaden dynamic range. However, these simplified assertions are not substantiated by theoretical evidence. The intricacies of sensor sensitivity and efficiency necessitate a more nuanced and responsible discussion than what is offered by the "size and capture" framework.

A quick search shows the EM5 II and the D5500 (above illustration) were launched in 2015. The EM5 II has a Live MOS CMOS sensor, and the D5500 has a standard CMOS sensor. Live MOS sensors have larger effective pixel areas than standard CMOS sensors. The D5500 has a 24MP sensor, and the EM5 II has a 16MP sensor. The total pixel area of the D5500 is 8% larger than the EM5 II, and the D5500 has 50% more pixels. This suggests that the EM5 II has a larger effective pixel area and possibly a lower noise floor. DxO test results show the D5500 has 13% more dynamic range, and the D5500 has a tiny ISO advantage in sports photography. No matter how hard you look, there is no equivalence between the EM5 II and D5500 to warrant an objective comparison of these two cameras.

Reviewers praised the sensor of the A7RII but later proposed that BSI (backside-illuminated) sensors do not significantly enhance sensor performance. The dynamic range of the Sony A7S MK3 has been enhanced by employing fewer and larger pixel areas, reducing pixel wiring, and achieving a lower noise floor (see Figure 3). This raises the question: what is responsible for the conversion of photons into electrons? Is it the dimensions of the sensor or individual pixels? Ultimately, the interpretation of this information is contingent upon its presentation to the audience.

Reviewers should provide a more detailed explanation of the "size and capture" theory. What's the basis for the claim that larger sensors capture more light? Does this suggest that larger sensors inherently have a greater capacity to attract light? It is important to clarify these marketing claims regarding "size and capture." Additionally, don't theoretical models suggest that the lens is engineered to cover the entire image sensor (sensor image circle) and that the sensor will saturate when properly exposed? I was unable to find any theoretical explanation of "size and capture" in the documentation provided by reputable camera or sensor manufacturers.

At what point are pixels too small to "capture" photons, or what is the minimum pixel area to make a noticeable image quality difference? The above DPR reviewer raved about an 8% difference between two sensors. Would a 224% difference cause a visible difference or excite this same reviewer?

The cameras in the above example had a uniform luminance perspective. Analyzing the results one sees both cameras captured enough "reflected light" (image data) to saturate their sensors. 

The actual differences between these two cameras are:

• The pixel area of each pixel in the EM1 III is 224%  larger than the Pentax QS-1. 
• The EM1 III has a Live MOS sensor, and the Pentax QS-1 has a BSI CMOS sensor. 
• That means the Pentax sensor has a 15% sensitivity advantage over the M43 sensor.
• What if the Pentax sensor has a higher native gain and requires smaller ISO steps?
• Fewer pixels on the Pentax Q means less pixel wiring and a smaller noise floor. 

It's incorrect to say a large sensor captures more light without reviewing its technical attributes. It is indeed reckless to hastily conclude that larger sensors capture more light or that size is the only consideration when evaluating digital cameras. It's critical to consider lenses, sensor attributes, supplier software, and image processors. Once again, it looks like marketers often highlight promotional priorities over a nuanced understanding of image sensors and digital cameras.

How many photographers differentiate between the technical and optical characteristics of sensors? For example, cameras equipped with varying sensor sizes exhibit distinct optical differences, while technical constraints, such as sensor saturation and signal-to-noise ratio (SNR), are unique for each sensor. This indicates that Micro Four Thirds (M43), APS-C, and full-frame (FF) cameras have distinct optical attributes and varying technical limitations. For instance, each image sensor is characterized by its own unique image circle, sensor AST, and noise floor. All sensors saturate when reaching the designed exposure level, and all sensors have a lower SNR in shadowed areas.

Conclusion

Photography is an artistic expression that makes us enjoy innovative marketing programs. However, it is concerning to note that photographers are experiencing a troubling trend in which they became comfortable with dubious marketing practices. This article aims to empower readers by challenging the prevailing idea that "technical information is generally superfluous."

Equivalence is a familiar concept for M43 photographers. For example, when reviewing the focal length (FL) of an M43 lens, we know Micro Four Thirds lenses require a 2X adjustment to match the focal length of FF lenses. Social media promoters remind us that an M43 aperture of f/1.8 corresponds to f/3.5 on FF lenses, suggesting that optical effects, such as background blur, should be comparable at these values. However, one may wonder why these same promoters refuse to discuss the intricacies of technical equivalence when comparing 24MP, 30MP, or 61MP full-frame cameras with 20MP (M43) sensors. For instance, does the concept of equivalence not imply that all technical variables should be equal to draw meaningful conclusions? This technical gap in the equivalence discussion explains the necessity of practices such as astroturfing in the current marketing environment.

Artificial intelligence has proven to have access to a significant repository of information. My ongoing conversations with AI are revealing more inaccuracies surrounding the oversimplification of the size and capture theory. Following is a short summary of a recent discussion I had with xAI.

See this discussion I recently had with xAI.

It's a shame to think FF advocates willingly

misinform many photographers...

The following variables are critical...

Two of the most critical considerations are modern image processors and computational features.