Spyder4Elite: Difference Datacolor/DisplayCAL

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  • #3567

    Vidar Hoel
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    I have to identical monitors: Eizo S2433W. One is attached to a laptop running Windows 10 with Datacolor’s software, and the other to a laptop running Ubuntu Gnome with DisplayCAL. After calibrating both monitors, one with Datacolor’s software and the other with DisplayCAL (both using Spyder4Elite), I see a clear difference between the two monitors, as you can see on the attached image. The monitor to the left is DisplayCAL – the one with less colors/vibrant colors/saturated colors.

    I used the same settings in both programs, 6500K, Gamma to 2.2, and 120cd/m2. I let both monitors have the default settings, but set whitepoint to 6500K and brightness so they both measured to 120cm/m2.

    Why is there a difference? Is it because of the software? The hardware? Some settings? And, ultimately, which is the correct one?

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    #3580

    Florian Höch
    Administrator
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    Hi,

    it’s not uncommon for different calibration & profiling software to produce different results, especially when looking at most vendor softwares where the aim seems to be more one of speed vs accuracy, while I’ve chosen the defaults in DisplayCAL with a focus on accuracy – but note that color managed software to view images may work differently under different systems as well, and I see in your screenshots that you are seemingly using Firefox to view photos, so how the browser is set up may influence what you see. I would switch to using one single calibration & profiling software solution. In case you want to use the DataColor software, you’d have to copy the profile from Windows to your Linux installation.
    In case you want to use DisplayCAL, I would also recommend to set profile quality to “high” – for curves + matrix profiles, there’s not really a calculation speed advantage compared to a lower setting. For most accurate results, I would also recommend setting the amount of patches to a higher value, e.g. 425 which would create a LUT profile.

    And, ultimately, which is the correct one?

    There’s several ways to build trust in your results. The most effective is to compare verification results to a measurement instrument with higher accuracy than what you have, but this is usually not an option for most people.
    The next best thing is to at least verify the closed-loop accuracy of the profile, using the “Verification” feature (you can also cross-verify the DataColor-generated profile).

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