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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Good news in a difficult year - all the macOS apps that I support - AccuRaw EXR, AccuRaw Monochrome, pcdMagic, CornerFix, dcpTool (both the GUI and command line version), DNG cleaner and pcdtojpeg - now are all available with native Apple Silicon versions for blazing fast performance on Apple's new "M1" processor. Download are in all the usual places.

Enjoy.

There's a whole slew of new camera support, including for Canon's new CR3 format.

Updates of AccuRaw EXR, AccuRaw Monochrome, PhotoRaw are now available on the Apple App Store.

pcdMagic for Windows - the only currently available app that can convert Kodak Photo CD images with correct color and at full resolution - is now available on the Microsoft Windows Store.

This great news for users:

The Windows Store version has a free trial mode that allows the app to be tested without any commitment. The Windows store handles all updates automatically. There's no need to keep track of license codes. The Windows store only supports the latest versions of Windows 10.
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As usual when new Leica cameras come out, I took a quick look inside a DNG from one of Leica's new Leica CL  cameras:

The camera name shows as "LEICA CL" The image data is 14-bit. There is no compression used in the DNG I looked at.  The DNG version is 1.4, with a "backward version" of 1.3. There is a reason for this - DNG 1.3 allows for opcodes, which Leica use for lens correction.
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So finally, after many years of searching, I have an answer to the question that torments all who go down the digital color rabbit hole.

This is from XKCD, brought to my attention via an article on the Digital Transitions website about the Phase One IQ3 100mp Trichromatic.

Back in January, when the new Leica M10 was introduced, there were claims that the improvement in dynamic range from the Leica M240 to the M10 was of the order of 1.5 to 2 stops.  At the time, I wrote that just by eyeballing the published images, I believed the improvement to be "closer to 0.5 stops than 1.5-2".

Much to my surprise, given what I had thought to be just a basic explanation of why dynamic range is a tricky concept, the post generated a lot of push-back. And I mean a LOT.

dcpTool has been available for quite a while as a command line application for Windows and the Mac. But now it available in the form of an easy to use Mac app, with powerful batch processing capabilities. dcpTool for the Mac is available from the App Store.

dcpTool allows you to:

Decompile DNG Camera Profile (DCP) files in XML. The XML can then be read and edited with a simple text editor. Recompile edited XML into DCP files Remove "Hue twists" from camera profiles.
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Many cameras embed lens corrections into raw the raw files that they produce. Generally, that's a good thing - straight lines stay straight, etc. For an example of lens corrections in practice, take a look at this post about the Leica SL.

But, as the saying goes, "there is no free lunch". Lens corrections also have some downsides:

Lens corrections result in a small reduction in sharpness.

Those of you that have read the Leica M10 raw file analysis post will know that M10 DNGs have more baggage in them that is typically the case for a Leica DNG. I've put together a little app to clean them up, called DNG Cleaner (Mac only for the moment).

AccuRaw users might have gotten a bit of a surprise recently - AccuRaw has turned into AccuRaw EXR, and is now at version 3.

The reason for the name change is that the focus of the AccuRaw product has changed a bit, based on what users were actually doing with it. AccuRaw has always been focussed on having highly linear color response, with no "hue twists" or other surprises in the color rendering.
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