Webinar: RGB Day! The Birth Of Color Photography & The RGB Color Process

May 20, 2021

Help us celebrate the 160th Anniversary of the color photograph, its history, and the RGB color model! Presented by colorist Hector Berrebi.


Series

May 17 is R G B Day! Celebrate and learn about the foundational color process.

RGB. It’s a color process that’s everywhere.

RGB is inside our camera sensors, the pixels on your monitor, the color picker in your grading tool, the math behind every Log transformation, the scopes measuring the pixels, film emulsion, color spaces, LUTs, sliders, and more.

Nearly everything we do in our craft can be narrowed down to the manipulations of these 3 ‘letters’. 

The RGB Color Process Celebrated Its 160th Anniversary On May 17, 2021

The very first color photograph was based on the RGB color process. From that first color photograph to today’s Rec. 2020 imaging standard  – RGB is central to image reproduction. But why should a Colorist, Cinematographer, Director, or Designer want to know more about this theory and its history? And… Why now? 

(drum roll)

160 years before we recorded this webinar, on May 17th, 1861, the great Scottish scientist James Clerk Maxwell and his friend, photographer Thomas Sutton, took the very first color photograph ever:

Tartan Ribbon - 1861 - first color photograph
‘Tartan Ribbon’, 1861, the first color photograph. By J. C. Maxwell & T. Sutton

That photo gave birth to the RGB color process that we’ve been using in our field for 160 years (and counting).

This extraordinary experiment by one of the greatest minds to ever live was the culmination of a study J. C. Maxwell conducted several years before (he studied the elusive nature of colors). Maxwell’s research narrowed in on a 2500-year-old question:

What Is Color?

And the exciting thing about the answer to this question? Maxwell’s discoveries gave birth to the endless tools and applications in our visual profession. From the terminology and culture cues that we apply in our workflows to the mysteries of our visual system – R G B is everywhere.

We owe Mr. Maxwell our profession!

70 years later, the CIE summed up our accumulated RGB knowledge in the famous horseshoe chromaticity chart still so prominent and critical in our work – coincidently celebrating its 90th birthday this year:

1931 CIE Chromaticity Chart
1931 CIE Chromaticity Chart is celebrating its 90th birthday this year.

The story of colors is a story of humanity’s endless curiosity and ingenuity, attempting to understand and recreate the world around it. Of course, it’s also the story of RGB.

Webinar Audience & Topics

This webinar was recorded on the 160th anniversary of the first color photograph. This is a beginner to intermediate level webinar suitable – for all colorists, editors,  filmmakers, cinematographers, and anyone else with an interest in color.

Not a math person?  Don’t worry!  This webinar will not go in-depth on scientific concepts and processes but will provide you with must-know information:

  • What is color – a (hard) thought experiment.
  • How colors were explained in ancient times
  • From Newton’s prism to Maxwell’s RGB – a 150-year exploration in understanding color’s true nature.
  • Human color vision and the famous 1931 CIE horseshoe – how RGB was quantified.
  • RGB is everything – How our tools and workflows follow Maxwell’s discoveries.
  • Your questions answered!

-Team Mixing Light and Hector Berrebi


Special Thanks to Our Raffle Contributors


Table of Contents

00:10 – Introductions
02:10 – Live Webinar Prize Giveaway Announcement
04:10 – Hector Berrebi Introduction
05:10 – Why are we celebrating RGB Day, today?
06:53 – What are you *actually* doing (in the real world) when you’re color correcting an image?
08:20 – A closer look at a modern display (and RGB in action)
12:40 – Why color is such a hard topic to discuss or explain (and the definition of Qualia)
17:03 – How the CIE standards organization defines light as being more than just a physical phenomena
18:21 – How it’s possible to see the color ‘red’ in an image when there are no actual red pixels in that image (this is the Twitter account of the experimental psychologist that Hector mentions)
20:22 – A super-abbreviated history of color theory through the ages (Theory of Colours, Kindle version, Amazon USA)
22:15 – Why color theory is important to professionals and why Maxwell’s photograph ushered in a new visual era
24:05 – Color, its relationship to light, and Sir Isaac Newton’s breakthrough in our understanding of light
26:00 – The very first color system, developed by Newton
28:11 – Newton’s hue system as visualized by David Briggs (huevaluechroma.com)
31:09 – Question: What about the correlation between colors and feeling?
33:22 – From Newton to Maxwell, a man who laid the foundation for much of modern science (and you probably never heard about)
34:51 – Mapping human color vision… with spinning tops – and proving the human trichromatic visual system
38:28 – Using three triangles to calculate a single point in a larger triangle – creating a color coordinate system
43:09 – A simple demonstration of RGB color theory basics
44:18 – No light? No color.
47:11 – If light is color, what frequency is pink?
48:12 – Fundamentals of the human visual system
50:02 – The (visual) difference between ‘real space’ and ‘display space’
51:14 – Photopic Vision: Non-linear receptors
53:02 – Maxwell’s first color photograph is a proof of concept
55:50 – Maxwell was brilliant. But he was also lucky.
61:54 – Black, white, RGB pixels, and luminous perceptual ratios (oh, my)
64:02 – Maxwell’s 160-year legacy to us, today
64:55 – The 1931 CIE Chromaticity chart
67:06 – How the Standard Observers, observed
69:36 – What is chromaticity?
70:40 – Why the 1931 CIE Chromaticity chart is the foundation of display systems
72:06 – Question: What does it seem camera systems have extra green representation?
75:10 – Upcoming SMPTE+ seminars
76:29 – Recreating Maxwell’s original photographic projection, using DaVinci Resolve (implementing Maxwell’s RGB color theory via the CIE Chromaticity chart)
79:19 – Fun with RGB in DaVinci Resolve using the Layer Mixer’s ‘Color’ composite mode
81:07 – The ‘Chromatic Adaptation’ ResolveFX plug-in
83:35 – Color correcting with Channels in DaVinci Resolve
84:09 – Thank you and goodbye


Comments

Homepage Forums Webinar: RGB Day! The Birth Of Color Photography & The RGB Color Process

  • This topic has 3 replies, 1 voice, and was last updated 1 year ago by Hector Berrebi.
Viewing 2 reply threads

    • Diover B
      Guest

      Hi, I was one of the winners in the quiz part.. but, couldn’t hear the next steps for claim the price.. pls hit me up.


    • Hervé Amiot
      Guest

      Thank you Hector for sharing your knowledge with that hint of passion. It is an interesting subject, although I did feel overwelmed on many concepts, but I understand that an hour and a half isn’t enough to explain everything in detail. Hope there will be a dedicated insight on this CIE chart because, being quite new to color grading, that sure is one of the scope that I cannot read or make use of yet. Even though I understand it as a representation of the colors actually present in the image, I don’t understand what it brings compared to the vectorscope. Also didn’t understand why feeding the splitter combiner cyan instead of green turned that yellow skin into a proper skin tone… Is it because you’re adding more blue so it negates the yellow, and if so, why adding that blue to the green channel instead of the red ? Last thing I did not understand (to be short because there some others thing that I just let go), is when you talk at around 51:30 about photocopic vision, saying that we are much more receptive to green and red than we are to blue, but the graphic doesn’t translate that, like the red is showed as being lower than the blue in terms of “Relative Intensity”…


    • Hector Berrebi
      Guest

      Hey Hervé , Salut.

      I’ll try to answer your questions shortly and as best as I can 🙂

      1. Yes! I am working on the 90 anniversary to the CIE chart. It has to happen!

      2. The CIE scope in DVR is somewhat misleading. In essence, it’s meant to show Gamut clipping – colors and areas in your image that exceed the boundary of your output color space – described as a triangle and tristimulus values of R G B – (which are in direct correlation to the pixels in your monitor and their maximum output). However, it doesn’t really – and can’t be trusted for this task in any critical environment. Since gamut is a 3 dimensional shape, its impossible to see it clip on a 2D triangle, that can only represent mid-tones (at most). A dedicated scope for Gamut excess and clipping, such as external scopes by Tektronix, is expensive and uses various measuring approaches for the task with exotic diamond, spearhead and arrowhead displays – see here for a nice infographic – https://download.tek.com/document/25W_15618_4.pdf
      and here for more in-depth read – https://download.tek.com/document/Color-Grading-Primer-Full_App-Note_2PW_28619_1.pdf
      As for how it differs from a Vectorscope – Quite a bit. The CIE shows Chromaticity and an xy plot, while the VS shows saturation and hue relative to a neutral center point an HSL/V plot seen from the top. You can’t evaluate an image with a CIE chart, not intuitively at least – but a glance at a VS should give any experienced colorist a good idea of what the image looks like.. on sat, hue, WB, BB, casts, colorfulness, and even more subtle aspects such as color palette and “feel”
      Page 2537 of the new DVR manual includes a nice explanation of the tool and its limits.
      Frankly, I don’t think it’s impossible for BMD to write a better Gamut excess tool, but I don’t think it’s simple either.

      3. The woman in the image had a strong yellow cast/excess on her skin-tone. If you split any well exposed skin, you’ll see it’s brightest on the R channel, and darkest on the B. If you brighten the G channel, you’ll make the skin look yellow (R+G), respectively by Multiplying the too-bright G channel with the usually darker (in skin) B channel – which in this case was even darker due to the excess Y (opposite of B) – Results in all values equal or lower than original (pixels are 0-1.. multiplying fractions results in smaller – darker values). This gives me a darker G channel to feed back into the combiner 🙂 Hope it cleared it for you.

      4. Misleading graphics. Red (L) relatively overlaps G (M) in our cone response think of the orange and yellow there as also being part of red, think of cyan as being at least half green. the numbers are spot on.
      Make a color solid in DVR, 255 B and 0 on other 2. then wipe it with a G solid of 255 and R of 255. the R and G are perceptually (and actually) brighter – lower them in the measured ratios of relative intensity and you will see them match up 🙂

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