High-sensitivity sensors for cameras like the OM-3

Last update: 29th August 2025

I have been observing YouTube channels focusing on the OM System OM-3. What sparked a discussion with ChatGPT were those explaining their preference for M43 cameras like the E-M1 III or the EP-7. It also seems like YouTubers feel compelled to justify positive reviews of the OM-3 or the OM-5 II. Does this indicate a trend or an accurate reflection of the M43 segment, or should we rather focus on the overwhelming positive feedback from those opting for smaller camera solutions?

My ChatGPT conversation highlighted technical weaknesses in the commercial layer's representation of digital camera efficiency. We reviewed the reasons why the OM-1 II or the OM-3 stacked BSI sensor is a high-sensitivity or pro-level sensor. It's rare to experience this amazing sensor with the OM System OM-3, as one expects this level of refinement from pro cameras like the OM-1 II.

I was working with ChatGPT to analyze the Olympus E-M1 III and the Sony A7 IV in an effort to find a more reliable way to express sensor efficiency than physical size. The E-M1 III has a Live MOS sensor, and the Sony A7 IV has a BSI sensor. The EM-1 III is the most capable pro-level camera from the E-M1 series. What differentiates the OM-5 from the E-M5 III is the TruePic IX image processor. The latest OM-1/OM-3 TruePic X processor and the stacked 20MP Quad BSI sensor offer significant advantages. This commitment to photography cameras has become a rarity in the past 5 years.

My discussion with ChatGPT revealed more about the 2-stop advantage of the BSI sensor of the OM-1, the OM-1 II, and the OM-3. We reviewed a more reliable way of rating sensor efficiency, including the unique ISO-to-SNR benefits from a deeper (in-focus) M43 depth of field advantage.

Did you know that the OM-1, OM-1 II, and the OM-3 have the same sensor?

Olympus EP-7 enhanced raw file converted and edited in Workspace.

A brief summary of my discussion with ChatGPT.

We started with basic knowledge and how to measure the efficiency of complex electronic parts. This know-how benefits all digital photographers, not only M43 photographers, as a good understanding of these basics will improve your ability to evaluate new product releases. 

I cropped the ChatGPT replies to improve the presentation.

The following ChatGPT reply reviews the above feedback and how it applies to image sensors. For instance, is physical size a good indicator of sensor efficiency, or do we need more?

The chances of a truly equivalent sensor size comparison are almost impossible. Equivalence means all optical and technical aspects need to be similar. Focusing only on the optical aspects of cameras will result in inaccurate comparisons. See this fun example of rating the bigger one higher.

The next question reviewed camera and sensor differences. Searching for a better way of expressing sensor efficiency, the aim is to quantify these differences in exposure stops. A more practical way is to say the difference between pro-level (more sensitive) and budget sensors is 2 to 3 stops? 

The next discussion examines the E-M1 III and the Sony A7 IV. The aim is not to compare them but to highlight the technical differences. AI questioning and probing techniques are crucial when searching for specific and theoretically accurate information. Poor questioning techniques generally leads to pleasing replies from most AI platforms. All information from AI needs to be verified and challenged. Use the AI replies in this article to start your own search for accurate information.

Please let me know if you have any questions.

ChatGPT reply: Part 1:

                        CFA = Color Filter Aray

Part 2:

Part 3:

I included the following replies, as they share relevant information for those wanting to improve their digital know-how. Much of what I say in my articles is reflected in these AI replies. There is much more to digital photography than what is presented in the commercial information layer. The secret is to focus on those aspects making a real difference for all digital photographers.

This link discusses the commercial versus factual information layers.

The next question discussed the 2-stop M43 depth-of-field advantage. For example, how do we apply this benefit to optimize our ISO-to-SNR ratio? This knowledge is only crucial if you want top results from digital cameras. Typical applications are landscape, low light, or product photography. Study my articles discussing the digital photography flow diagram for digital cameras.

The final question considers the 4th exposure variable in the exposure formula. Yes, it is possible to manage shadow and highlight clipping. The sensor's dynamic range is only another variable.

Folks, there is no need to apologize for the M43 segment or when recognizing that there are almost no visible image quality differences between most cameras. The OM-3's shadow details did benefit from the BSI sensor. What surely makes a difference is the new TruePic X image processor and BSI sensor combination. That said, I get great results from both my E-M1 III and the OM-3.

If physical sensor size is not a reliable indicator, what criteria should we use to rate digital cameras? As said, budget sensors are 1 to 2 stops less sensitive than professional sensors. The key difference between digital cameras is advanced features and autofocusing options that enable us to repeatedly capture great results in diverse conditions. Some of these differences are not applicable to casual or hobby photographers but are more relevant to professional photographers.

Olympus EP-7 enhanced raw file converted and edited in Workspace.

The camera's image processor customizes critical image quality markers, such as the gamma curve, white balance calculations, image sharpening, image color priorities, and fine detail processing. This makes it factually incorrect to claim that larger sensors capture and produce more image quality. It is better to highlight more accurate sensor and image processor roles and definitions?

I understand that AI is still developing and is not a mature and reliable service today. My intention is not to suggest AI as a reliable source of information. Nothing beats personal engagement, experience, and knowledge. My recommendation is to learn and to test everything you read, see, and hear.

See this interesting image quality test I did with 15 cameras - link.

Best

Siegfried

How much of a difference does Pixel Area make?

Last Update: 4th May 2024

Introduction.

My son said I may try his Sony ZV-E1 while he tried my Fuji XT-5. The Sony ZV-E1 uses the same FF 12MP BSI sensor as the Sony A7S III. A camera like this should be tested. I would have liked to include my Fuji XT-5. The test results are exciting and reveal much about what to expect from various cameras. For example, the Sony ZV-E1 pixel area is 5 times larger than the Olympus E-M1 III and almost 20 times larger than the Olympus XZ-2. How much do these pixel area differences impact the IQ of these cameras? What should we look for, and how will you test these cameras?

Sensor Sensitivity is an indicator of the sensor's Optical and Quantum efficiencies. That means larger pixel areas capture more light, right? The secret is to study shadow details because increasing sensor sensitivity means capturing more shadow information. What kind of shadow differences do you expect to find between the Sony ZV-E1 and an older Olympus XZ-2? While I am not testing for noise, what do you expect to see from these 2 cameras? Does the sensor's pixel control wiring add noise?

I included several Olympus cameras in this test. We learn much from the pixel area variances between these cameras. For example, the pixel area of the Olympus E-1 is three times larger than the EM1 III. It is sometimes easier to simulate sensor differences with your existing camera collection.

Preparing my Test Studio

I created a test "studio" with a 4EV exposure difference between the highs and lows and measured the brightest point to set the exposure with my camera's spot meter. That means each sensor's Saturation and SNR were 4 stops lower in the shadows. Study the photon-to-electron graph in this article to learn more about sensor saturation and SNR. Every digital photographer should know this graph...

Each camera's sensor is technically different. My knowledge of digital cameras helped me plan pixel area tests. For example, pixel area reveals more about sensor performance when comparing digital cameras. Sensor size (diagonal measurements) is an indicator of the sensor's optical characteristics. I created the chart below to illustrate the pixel area variances of the cameras I tested.

The chart lists pixel count in red. Why is it important to consider pixel count? Because pixel count determines the sensor's total pixel area. For example, go to the 12MP (FF) sensor on the horizontal axis and compare its pixel area to the 12MP (1/1.7") sensor on the vertical axis. You can compare all the sensor sizes in this chart with this technique. That means we are evaluating pixel area and not sensor size. For example, how much more detail should the Olympus E1 capture over the E-M1 III? Does the sensor's quantum and optical efficiencies influence these camera comparisons?

The only benefit of sensor size is commercial. It's technically meaningless and reveals nothing about the sensor's ability to capture more data. For example, it's better to focus on the sensor's diagonal measurements. The reason is the lens image circle has to cover the complete sensor. This explains the more light theory confusing so many FF enthusiasts or the equivalence factor when comparing the optical differences between M43, APC, and full-frame cameras. See the table below for more.

What is the best way to compare these different pixel areas? Take a few minutes to prepare yourself by selecting a few cameras (pixel areas), and writing down what you like to learn from these tests. For example, how many more shadow details do you expect to see from the 12MP FF sensor over the smaller 1/1.7" version? Also, study the Fuji X-T5 or Medium Format 100MP pixel areas and explain why the shadow details of these cameras would be technically similar to 20MP (M43) sensors. Why would one expect to see more shadow noise with these two Fuji cameras (sensors)?

Olympus C-770UZ  (4MP) - ISO64, f3.2, 1/160 - OOC JPEG and not edited...

Let's study these different test images...

The noise filters were OFF while taking 4 RAW images with each camera. The Enhanced RAW Files were converted in Workspace with no noise reduction (NR). I used the Photoshop 2024 Raw Converter with no NR for the other. I upped the shadows to reveal more captured data. All the cameras were optimized to deliver maximum detail and IQ. One typically expects less visible noise from a saturated sensor and a higher SNR. That said, these comparisons were all about capturing detail...

The test images are best viewed on a large display. Click on the first image...

The following samples are crops of the above images. This will assist readers to find more details. I only upped the shadows and prepped the images for the web. I did no color corrections or NR. These converted raw files reflecs the captured sensor data. I appreciate that each person experience the results differently. Knowledge and regular practice is good advice for consistent results with different cameras. I expected larger IQ differences from 20 years and 20X pixel area variances.

How does one explain the increased noise levels of the E1, E500, E-620, and EP3? One would typically expect less noise with fewer pixels and less control wiring. The noise floor of these older sensors are larger because the the quantum efficiencies (photons to electrons conversion) and control wiring are not as optimized as newer sensors. ETTR is more effective with older digital cameras.

How would you explain the increased noise levels of the Panasonic LX-10?

What were my camera configurations? I used the 17mm f1.2 lens on my M43 cameras and the 50mm f2 macro lens on my 4/3rds DSLRs. The Canon 6D II had an EF 35mm f2.0 lens, and the Sony ZV-E1 had a 55mm f1.8 Zeiss lens. That means I used my tripod distance to the subject to compensate for lower megapixel sensors and the different focal lengths. I used Manual Exposure with an Aperture of f3.5 or f4 for these cameras. I also used the 2sec timer and +1EV ETTR for each camera.

I used the same white balance (marker) when converting the raw files.

Conclusion

You don't need to be an expert to see the Olympus XZ-2 and Sony ZV-E1 results are very similar. For example, I couldn't find 20 times more image details for the Sony. That means the Olympus XZ-2's image details compare well with the Sony ZV-E1 and its 20 times larger pixel areas. The 20-year age difference between some cameras also didn't make a 20X difference. Finally, less than 100% pixel area differences seem insignificant. That means one can ignore the sensor sensitivity differences between M43 (Live MOS) and APC (Standard CMOS and BSI) sensors. What makes a real difference is knowledge, lens selections, and regularly using Workspace and one's Olympus camera.

I used the Olympus E-M1 II for years and the E-M1 III for eighteen months. This is an exceptional camera with excellent IQ, speed, and functionality. The most fascinating part about them is the 20MP Live MOS sensor. I would love to see the specs Olympus used to find this sensor 12 years ago.

What do we learn from this comparison? We simply can't trust those repeating the same "size and capture" phrases. The Sony ZV E1 is a top performer and delivers excellent image details and shadow data. We also saw that the Image Quality differences between cameras are way less than expected. Is this the reason why photographers are rediscovering older cameras and sensors? For example, the TruePic processors and 16MP sensors in the E-M1, E-PL9, E-M5 II, and E-M10 II/III are excellent. Photographers are better off evaluating costs, functionality, speed, application, and form factor.

The following 4 samples are the final edits with Workspace, Photoshop, and Photolab 6. I did them to help readers get a feel for the various edited versions of the above samples...

Olympus E-1 with 50mm f2.0 lens - ISO100, f4.0, 0.6 seconds (1EV ETTR) - Raw converted and edited in Photoshop.

Olympus E-1 with 50mm f2.0 lens - ISO100, f4.0, 0.6 seconds (1EV ETTR) - Enhanced Raw converted and edited in Workspace.

I used the standard NR filter on the above image. Workspace has an older NR filter for older cameras like the E-1. The E-410 and newer models have a different and more advanced NR filter...

Olympus EM1 III with 17mm f1.2 Pro lens - ISO100, f4.0, 1/2 seconds (1EV ETTR) - Raw converted and edited in Photoshop.

Those photographers who make a habit of improving their Enhanced Raw files and Image Editing skills enjoy an advantage. The benefits of improving one's knowledge and camera and editing skills are remarkable. I often write about the benefits of converting your Enhanced Raw Files with Workspace. Also, see this video reviewing the Enhanced Raw Format and Workspace.

Olympus EM1 III with 17mm f1.2 Pro lens - ISO100, f4.0, 1/2 seconds (1EV ETTR) - Raw converted and edited in Photolab 6.

Final observations. Study the "deeper" shadows between the above flowers to see the details from these cameras. The Canon 6D II revealed more shadow details than others. The last four edits are interesting. One can spend hours editing these raw files for different results. DxO PL-6 or 7 is a good solution for older Olympus raw files, especially if you prefer basic conversions and editing.

See this article where I comment on 12MP versus 100MP printed samples.

Also, see my Workspace firmware update page - link.

Best Siegfried