1. In this post, I’ll look at the color response of Capture One, Lightroom and Aperture against an image of an actual GretagMacbeth test chart, as cteated on a Nikon D80, rather than the Leica M8 I used in the previous post. As was the case last time, I first adjust the contrast and exposure setting on each program to exactly match expected values of the lightest and darkest monochrome patches on the GretagMacbeth chart. This exactly matches the exposure of the real images to the effective exposure of the synthetic image. As was the case for the synthetic images, all the test results are on a 0 to 100 scale, and represent the difference between the expected value as derived from the color values of the GretagMacbeth chart and the actual values measured. So, for example, if the red bar of the “Cyan patch” shows a value of -5, that means that the actual measured value of the R component of the RGB values as read out by the software in question was 5 units less that the theoretical value.

    In the case of Lightroom, relative to the deviations in the M8 actual image from the last post, we see less negative deviations overall, indicating more saturated colors, and a significantly more saturated red patch. However, overall the picture is relatively similar to that of the M8. This starts to imply that differences in color rendering really are more to do with the raw conversion software, and less to do with different cameras.



    Aperture shows a somewhat different picture. The 1.1 rendering of the M8 showed some large positive spikes in the blue component of several patches, especially the yellow patch. This doesn’t appear on the D80 rendering. However, the red component is the cyan patch is quite negative. The 2.0 rendering shows considerable change relative to the previous V1.1. Firstly, most of negative deviations have gone – the largest negative deviation anywhere is in the red component of the cyan patch, but even this is well down from the previous value. Overall, the 2.0 D80 rendering appears significantly better controlled than the previous version.



    Capture One is an interesting case. At a first glance, it appears that the rendering is simply a considerable distance away from the theoretical values, almost all color components appear to be greater than the theoretical values would indicate. The peak deviations are over 20 units, in sharp contrast to Capture One’s rendering on the M8 image, in which the deviations are of the order of 10 units. However, a closer look shows that what has actually occurred is that the pattern of deviations has remained very much the same, but that their magnitude has grown, and been offset in a positive direction. What this amounts to is that the image is considerably brighter overall. This is a strange result, and one that I’ll come back to in my next post.

    For the moment ignoring the issue of the Capture One brightness, we can draw two conclusions at this point:

    1. Most of the color variation that we see appears to be due to variations in the calibration of the raw converters, rather than variations between camera brands. The Lightroom M8 and D80 color renderings look a more alike than, for example, the color renderings of the M8 using Lightroom and Capture One.
    2. Aperture 2’s color rendering appears to have been significantly improved, at least in a technical sense, relative to the previous versions of Aperture.
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  2. In the previous part of this mini-review, I looked at the color response of Capture One, Lightroom and Aperture against a synthetically generated GretagMacbeth test chart. In this post, I’ll look at the response of the same programs against an image of an actual GretagMacbeth test chart. The process that I will follow for the actual image is a little different to that for the synthetic image. In the case of the synthetic image, I made no adjustment whatsoever to the image – the readings are exactly as they appear when the image is imported into each program. For the real image however, I first adjust the contrast and exposure setting on each program to exactly match expected values of the lightest and darkest monochrome patches on the GretagMacbeth chart. This exactly matches the exposure of the real images to the effective exposure of the synthetic image. As was the case for the synthetic images, all the test results are on a 0 to 100 scale, and represent the difference between the expected value as derived from the color values of the GretagMacbeth chart and the actual values measured. So, for example, if the red bar of the “Cyan patch” shows a value of -5, that means that the actual measured value of the R component of the RGB values as read out by the software in question was 5 units less that the theoretical value.

    Relative to the synthetic image, Lightroom was, as expected, very close to the theoretical values for the GretagMacbeth chart. Versus a real image however, it shows significant differences, most noticeably in the red patch, where it has significantly more blue and green than might be expected. At first sight, this is a somewhat counter-intuitive result, as while the greater levels of green and blue indicate a more saturated color than the theoretical representation; Lightroom in general has a reputation for excessive red. It’s only in the green patch that there is significant excess red. This would imply that when the complaint of Lightroom’s “excessive red” is made, it is probably more of a complaint about the saturation of reds in the image, rather than an excess of the red color component.




    Aperture shows no clear pattern of greater or lesser overall saturation, but does show two interesting characteristics. Firstly, the green components are still very much less than are the case for Lightroom, but at the same time the absolute variation from the theoretical value is far less – versus the synthetic image, the variation was -15.3, but against the actual it is only -6.3. This suggests that the Aperture calibration for the green components in a real image is probably better than Lightroom’s, even though the Lightroom’s better matches the synthetic image . Secondly however there are significant variations in the blue component, especially in the 1.1 profile. The newer 2.0 and DNG profiles show color rendition that is a lot closer to expected values that the previous version. This is consistent with Apple’s statements that the raw conversion subsystem has been substantially revised and improved in the new version. Overall, the actual M8 inages converted with the Aperture 2.0 profile is a better match to theoretical values than either the previous version of Aperture, or Lightroom.





    Turning to Capture One, the most significant feature of the charts is the absence of “negative spikes” – while both Lightroom and Aperture have at least some color patches where at least one color is significantly less than the theoretical value, Capture One is relativley better controlled in this respect – only in the yellow patch is there a significant negative deviation. In addition, this control of negative peaks isn’t at the expense of spikes in the positive direct; no spike exceeds 12 units. It’s also interesting to note that in the three primary patches, the red component is within three units of the theoretical value in the red patch, and the green in the green patch and the blue in the blue patch are similarly well controlled. Thus, while Aperture is overall closer to the theoretical values, Capture One is perhaps “closer where it counts”.



    In my next post, I’ll take a brief look at color rendering for the same three programs against an actual image from a Nikon D80, so as to get a feeling for whether the patterns here are M8 specific, or relate more to the programs in question.
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  3. At long last, here’s the comparison of color rendering promised several weeks ago – between work and the display board in my main PC failing, this has taken longer than I’d expected. This post compares the color rendering of Lightroom, Aperture and Capture One versus a synthetic test image. That image was created by taking the raw image from a Leica M8, which is in DNG format, and then replacing the contents of the image with a synthetic version of a GretagMacbeth 24-patch color chart. This can be done because DNG format files contain all the color calibration information that’s required to go from the Camera’s raw image space to a real image in the two ColorMatrix matrices. So the synthetic image is built by taking the l*a*b* color values for the GretagMacbeth test chart, and reversing the calibration matrixes in the Leica DNG file. This, btw, is being done using a modified version of CornerFix – I’m currently debating whether to include the synthetic image creation functionality in the next official CornerFix release.

    The synthetic test image is what a “perfect” M8 would show. But “perfect” here means an M8 that matches Leica’s calibration matrixes. However, there is no one single best calibration for a real camera. Pretty much all camera calibration is done via a three by three matrix. Using that, you can dial in any three particular colors exactly. So, for example, you can get the red, blue and green patch on the GretagMacbeth chart down to the last decimal point. If sensors were perfect, that calibration would also mean that every other patch would also be calibrated. However, in a real sensor, there are a whole lot of imperfections – among other things, the filters in the Bayer matrix aren’t ideal, so colors bleed between each other, and the sensitivity of the sensor itself varies with the frequency of the light striking it. So, even if you dial three patches in perfectly, the others will be out. So practically, what camera manufacturers and raw developer software writers have to do is to find a calibration that is a compromise across a whole range of colors. However, because people are more sensitive to certain colors being out (e.g., skin tone, foliage, etc) that compromise is often weighted in favor of the sensitive colors.

    The M8 test images can be found here: http://chromasoft.googlepages.com/referenceimages

    The charts below show the difference between the theoretical color values that we should see for a selection of six of the more important color patches, and what we actually get. So, for example, if the red bar of the “Cyan patch” shows a value of -5, that means that the actual measured value of the R component of the RGB values as read out by the software in question was 5 units less that the theoretical value as shown in the spreadsheet I discussed in the last post. In all cases, the scale is 0 to 100.

    First up is Lightroom. It shows minimal deviations from the theoretical values – all the values are within 3 units. But this shouldn’t come as a surprise – Lightroom internally uses the exact same color model as the DNG file, and we know that Lightroom uses exactly the same color calibration as the Leica DNG’s have embedded into them. The minor deviations that we seeing are really just slight imperfections in the tone curve and in the color temperature interpolation process that Lightroom uses.



    Next up is Aperture. There are three Aperture graphs, the first for Aperture V1.5.4. In addition I also have graphs for Aperture 2.0, which came out a few days ago. Aperture 2.0 provides four “Raw Fine Tuning” settings, “1.0”, “1.1”, “2.0” and “2.0 DNG”. I checked, and color rendering from the old 1.5.4 and what you get by setting “1.1” in 2.0 are indeed identical. Firstly, all of the Aperture settings have lot less green in the red patch than Lightroom, and less red in the blue and cyan patches. The 2.0 results are not much different to the 1.5 results; a little bit less red in the blue patch, a bit less green in the red patch, but far less blue in the yellow patch.


    The “2.0 DNG” setting is more interesting. There doesn’t seem to be much documentation on what it does – the Apple aperture site itself is silent on the subject, and various third party sites have words to the effect of “changes to the image using the 2.0 DNG converter are made based on the DNG specification of the file”. This implies that rather than using the Aperture color conversion parameters, setting the DNG mode will give you the colors as set by the ColorMatrix values embedded in the DNG. As it turns out however, that’s just not the case – if it were, we’d see values that looked like Lightroom, but what we see are just some subtle changes to the “2.0” profile. Although visible if you change the setting on the fly, the change is actually more subtle than the change between 1.5 and 2.0.




    Finally, there is Capture One. During the course of this process, Capture One 4.0.1 came out; the results shown here are for 4.0.1, but they are identical to those for 4.0; as far as I can tell, no changes have been made to color rendering between versions. Capture One provides two profiles, one Generic, and one UVIR, designed to match to the M8’s color rendering when mounted with a UVIR filter. While the differences between these two are there, they are quite subtle. Overall however, there are significant differences to the rendering of either Lightroom or Aperture. Capture One shows less red for most patches, especially the red patch, but more red in the cyan patch. Finally, there is generally somewhat less saturation for most colors. This is broadly consistent with most people’s views on Capture One’s rendering as being “less red” than Lightroom.

    In the next post I'll show the same charts for actual rather than synthetic images.
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