Category Archives: Tests

Equipment, Reviews, Tests

Looking at Canon 5Ds Raw Files: Noise and Dynamic Range

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(Note: The images were not included in the original post, which instead included text links only. The images are now part of the post.)

I just took a break and had time to play with a Canon 5Ds raw file that I found on the web. (Anyone wanting to look at files from the 5Ds should head on over to that link right now — there are something like 90+ files to look at.) It was made with the 5Ds at ISO 100, f/8, 1/400 second. It isn’t clear what lens was used, but it appears that it could have been either the 50mm f/1.8 STM lens or the 24-70mm f/2.8 II.

I opened the file in ACR. I made no adjustments to curves, color, etc. I let ACR automatically correct for CA. Default ACR sharpening used at 15 with masking at 50.

I brought the converted file into Photoshop as a smart object to allow for non-destructive re-editing in Adobe Camera Raw (ACR). I confirmed that shadow areas along the waterline of the boats have luminosity values of 0 — I did this by checking the Lab color representation and watching the L value, which hits 0 in several spots. The general area is shown by the rectangle in the following image: Continue reading Looking at Canon 5Ds Raw Files: Noise and Dynamic Range →

Equipment, Tests

New Canon 5DS R DSLR: A Printing Test

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(Updated: May 2015)

In February 2015 Canon announced the new EOS 5DS DSLR bodies in two versions: the EOS 5DS and the EOS 5DS R The “R” model does not apply anti-alias filtering (AA-filtering) to the image. This is said to have the potential to optimize image sharpness in some cases, though it increases the risk of aliasing/moire artifacts in photographs that include fine patterns such as fabric, screens, and similar. Both versions of the camera have 50.6MP sensors, which more than double the number of photo sites compared to previous Canon 21MP and 22MP full frame sensors.

A big question for people considering this camera is how much potential for image improvement will come from the higher-MP sensors. My feeling is that the improvement should be meaningful for photographers who already push the upper boundaries of potential print size from full-frame image files, but that the increase in MP will not likely mean much to photographers who don’t do this. Since I’m in the former category — and therefore quite interested in the new bodies — I wondered how this might play out in an actual print. (Prints, after all, are where the rubber meets the road with high MP cameras.)

I did not have access to raw files from the new camera at the time of this test, however Canon had made full resolution jpg files available online. (RAW files were not available at the time I conducted the test, but they are not necessary for creating a high quality print, as long as extensive post processing is not used.) I downloaded “Image 2” from the link, which appears to be a straight-from-camera jpg image made with the Canon EF 16-35mm f/4 L IS lens at f/11, 1/500 second, at ISO 200. The image is an aerial photograph of a dense downtown area, with many buildings and other details, including some that should reveal moire artifacts if they are going to be an issue.

My entire workflow with the image was as follows:

  1. Open the Canon jpg file in Photoshop CC.
  2. Resize to 30″ x 45″ at 300 ppi
  3. Select a letter-size section of this resized image and crop it out of the full image. Since I am interested in detail reproduction and how the non-AA-filtering body handles potential moire, I took a section that included the radiating spokes of a ferris wheel against the linear forms of buildings.
  4. Apply my customary output sharpening for prints.
  5. Keeping the resolution of the 30″ x 45″ image, I printed the small section on 8.5″ x 11″ Epson Ultrapremium Lustre paper using my Epson 7900 printer.

The results?

If I handed most people the letter-sized printed extract they would probably think, “Not a bad print — not great, but fine.” But they would not likely notice that they were looking at a tiny fraction of an original 30″ x 45″ print. Skillful photographers and printers who looked closely would be able to see some things suggesting this… but once they heard that it was from a 30″ x 45″ inch print, I’m positive that they would join me in being very impressed. Detail is excellent, especially so for such a gigantic print size. I see no obvious examples of moire artifacts, and I’ve looked closely. I do not not see any smearing of colors, and I can see no noise whatsoever in the print of this detailed image. (I cannot say whether or how much noise would be available in an image of a subject with continuous or smooth gradient tones.)

Since this looked so good, I decided to take things to further and repeat the process — but this time resize to 60″ x 90″ at 300 ppi. For those who don’t know, that would be a very, very big print — four times the print area of the 30″ x 45″ print. Again I selected a letter-size subsection of the final huge image and printed it.

The results?

At this huge size I can certainly see that the image is softer — though whether that is a result of using a 16-35mm ultra wide lens or from the resizing or a combination of the two is open for debate. If you looked at the letter sized print and did not know that it was a crop from an image 5 feet tall and 7.5 feet wide, you would think it was soft. If you made the full print (which I’m not equipped to do!) you would be very impressed. I still see no aliasing/moire artifacts. I do see some slight color smearing in a few areas where there is a sharply delineated edge to a colorful area.

Bottom line: I’m confident that photographers using full frame images to make very large prints are going to like the results from this camera a great deal. I am certainly going to get one — in fact, I have pre-ordered a 5DS R from B&H. (You can do the same using the following links — the cost to you is the same, but you’ll help support this website and article like this one. Thanks in advance!)

Notes:

  • Update 5/15/15: Since I first posted this article much more information about the cameras has become available, including reports and raw files from parties using late-beta versions of the camera. I have had a chance to look at some raw files and they seem quite good to me in every way that matters to my photography.
  • Update: The cameras are now available for pre-order (as of 3/23/15), and I posted an article with more information more about the cameras.
  • The original version of this article incorrectly stated that Canon’s example file was made with the new EF 11-24mm f/4L USM lens. The article has been edited to correct this error.
  • As a side note, the level of detail in the sample image speaks very well for the resolving power of the Canon EF 16-35mm f/4 L IS lens.

5Ds and 5Ds R Articles:

G Dan Mitchell is a California photographer and visual opportunist whose subjects include the Pacific coast, redwood forests, central California oak/grasslands, the Sierra Nevada, California deserts, urban landscapes, night photography, and more.
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Commentary, Equipment, Technique, Tests

“My Photos Are Soft!”

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So, you have a camera or lens that you think is not as sharp as it should be. If you are already expert at these things, what follows is not for you – you already know how to analyze the problem, you can anticipate possible causes, and you know some of the pitfalls of looking at the issue in unrealistic ways. But if you aren’t certain about how to deal with the issue, perhaps the following might help… so feel free to read on.

Perhaps you just got a new lens or a new camera and you don’t think it is performing as you expected. Or perhaps you have long suspected a problem with your equipment. On the other hand, maybe some gear that you have used with confidence for a while seems to not work as well as you recall it working in the past. It can be tempting to blame the equipment – and in some cases you may be correct – but it is a very good idea to first try to analyze and understand the problem and look for other possible causes… and solutions.

It is critical that you try to control the variables that might give rise to the issue, and then to try to a) determine if the problem is real, and b) figure out specifically what might be the cause. The range of possible causes is larger than you might imagine: problems with the camera’s autofocus (AF) system, an out of adjustment or “weak” lens, less than optimal choice of lens settings, issues with camera stability, insufficient care with the use of AF, using the wrong AF settings, aperture choices, shutter speed choices, subject motion, and more. While a real equipment problem is a possibility, it is probably at least as likely that the problem lies elsewhere. Fortunately there are ways to wade through this minefield and develop some rational understanding of what is going on.

What follows is a sort of ad hoc description of how I might approach this. It is not meant to be the only way to deal with such issues, it leaves out some possibilities, and the sequence could be changed around in some ways. Continue reading “My Photos Are Soft!” →

Equipment, Ideas, Tests

Experiment #2 Revealed

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Yesterday I posted “Experiment #2: What do you see?,” in which I shared six image files comprised of three identical pairs of images and asked volunteers a) whether they saw any differences among them when viewed in their web browsers, b) to describe any differences that they noticed, and c) to try to identify the pairs of identical images. As describe in the original post, all of the images came from the very same source file – e.g from a single exposure – and were processed identically with the exception of one variable that was not identified.

Here are the 100% magnification crops from the three source images:

The differences among them are obviously in the amount of noise that was added to the image. No noise was added to the first image – any noise there was in the original capture. 10% level “Uniform” noise was added to the second image in Photoshop. 20% “Uniform” noise was added to the third image in the same way.

While I could have varied camera ISO to produce actual camera-generated noise, doing so would have also produced other variations in the images that would have given secondary and possibly misleading cues as to the differences between images. This most certainly would have affected part c) of “the question” as outlined above. While recognizing that noise added in post is not going to be exactly the same as noise produced in camera, I did try to ensure that the noise would at least be of a type and level that would clearly cause concern if the camera did produce it.

The soft photograph was chosen to avoid masking the noise with a lot of other sharp detail – this image provides very smooth gradients from black to white, where noise is typically easier to detect. I also chose this image because it is nearly – but not quite – monochromatic. This meant that I could increase the effect of the noise by using color noise rather than limiting to monochromatic noise – and that the color noise would tend to be more visible against the nearly monochromatic background.

While quite a few folks reported that they didn’t see any difference among the image when viewed in their web browsers – and, frankly, this did not surprise me – some did report noting differences. Test subjects have been known to both correctly identify real differences… and to think they have seen real differences where none existed. With that possibility in mind, I was interested to see how accurate the “perceptions of difference” might be, hence the challenge to find the pairs of identical images. The idea here is that if one can really see differences between images that one should then be able to categorize the images accurately based on those differences. I won’t comment here on whether any individuals were right or wrong, but here are the six images grouped as identical pairs.

No noise added:


10% noise added:


20% noise added:


A good number of readers asked, “What is the point?” A few even were upset at a test of something they regard as settled – e.g. that noise and other small artifacts become imperceptible when a large image is reduced to typical web sizes. (In this case each pixel in the jpgs is the average of close to 100 pixels in the original file.) However, I can say for sure that this issue is not resolved in the minds of all photographers nor in the minds of many who are making purchase decisions about cameras for themselves or for others.

My thesis was essentially that very significant amounts of noise that would be clearly visible in large original files at 100% magnification will be indistinguishable from files that have far less noise but are otherwise identical when the files are reduced for typical web site use.

A direct “point” might simply be that if you reduce 21MP full frame photographs containing large amounts of noise to 600 pixel width high quality jpg files viewers of the images on the web seem unable to reliably notice the differences in noise levels. You could reasonably extrapolate from this that if your main reason for shooting photographs is to share them on the web, noise levels in the camera may not be an important decision point for you as you shop. Though you cannot extrapolate the following directly from this test, I believe that shooters who mainly share jpg images or perhaps make letter-size prints will not see any significant image quality benefits from getting really high-end cameras. If noise levels as different as those found in this experiment cannot be discerned then the quite small differences in noise between two brands or models of camera are likely to be completely insignificant in images viewed online at typical dimensions. (If you make very large prints on a regular basis then your issues will be different.)

For my part, even though I created the images, I cannot reliably tell them apart by looking at them! When I look up my record of which image was treated which way I think I can see the difference, but I’m pretty certain that if I had to try to pair the identical images I would be unsuccessful. (Note: if you view the images one above other on this page you will think they are different due to viewing angle differences on your monitor. Go to the original post to see them displayed successively in the same location on the screen.)

(Experiment #1 tried something similar, though in that case the variable was the “sharpness” of the original image file.)