squish7.com /color

LINKS   Crayola Crayons  .  Wikipedia Color  .  Wiki RYB Color  .  Wiki RGB Color

Color is one thing that must be re-thought when we think about a universe founded on perfect balance and opposition.  Color (as with all life) results from what could have remained nothingness (basically grayness) tearing itself into all being in equal directions.  Our consciousness only exists because of an equal consciousness we're tearing off of (we see opposition all around us, war and peace, love and hate, why wouldn't the ultimate opposition exist?).  If we can understand this perfect opposition and hence everything inbetween through the microcosm of color, we can better understand the spectrum of complex emotion and life all around us.


To start understanding our perfect inverse, we'll begin with the horrifically deceptively simple task of trying to invert a simple digital image.  Here's Joe.  Joe has a happy life being a black stick figure with a yellow smiley face, on green grass, blue sky, and white clouds, and he is allowed to exist (as we are) only because there exists a perfect un-Joe.  Let's give him a good name, since he's a living being just like Joe is; we'll call him 'Eoj' ('Joe' reversed).  What does Eoj see and look like?  All we have to do is invert the picture; sounds easy, right?  Not really.

We'll try two major color systems (note that I'm not commenting on the science and general workings of these systems, but only examining whether and how they help us understand what a pure "visual inversion" of our inverse consciousness looks like).  We have Red-Yellow-Blue, the mixing wheel, the one we're used to from gradeschool, where you mix red and yellow paint and get orange, and so forth, observing the color wheel below to the left, where red is green's opposite, etc.  So it seems a simple task to just invert each pixil, but I'm still looking for a program that can do this.  Most programs opertate under the Red-Green-Blue monitor, which invert differently, as seen here.

color wheel wheel RYB inv wheel RGB inv
Color Wheel RYB Inverse RGB Inverse

From intuition, I think that white is black's pure visual inversion, so there's no argument there, and the systems agree.  But how do I know what a perfect inverse color looks like?  I have no way of testing this experimentally, and only my intuition to go on, and two of our main scientifically-based color systems seem to disagree with eachother.  I really can't have much idea initially whether they might both be flawed, they both sort of look inverted to me, but they're all we have to go on, so let's examine them.

Here's one thing that casts a lot of doubt on the RGB model: when we see a wider color spectrum inverted, we see that a whole entire side of the RYB color wheel has turned mostly blue.  This certainly can't be correct, I can clearly see that there are a variety of original colors, so the inverse colors that Eoj sees should be equally spectrumed.

color wheel wheel RYB inv wheel RGB inv
Color Wheel RYB Inverse RGB Inverse

So maybe we're leaning towards trusting our RYB instincts if anything.  But MS-Paint, Adobe, Jasc, and Gimp, all invert based on RGB, so we can't even do the should-be-utterly-simple task of doing this automatically.  We'll have to invert RYB manually for these simple pictures (i.e. selecting the proper color using the fill bucket in paint and filling in the areas ourselves, which we clearly could not do to a 10,000-pixiled complex image) until somebody tells me how the hell to invert a RYB picture.  Here's our first look at Eoj in each system.

Joe Joe RGB inv Joe RYB inv
Joe Eoj - RGB inv Eoj - RYB inv

Notice that in the original, the sky seems lighter than the grass, so it should be darker than the grass in the inversion.  But in the RGB the sky looks lighter, and in the RYB, they still look about the same.  Also, the colors in the RYB look very similar; we've lost the sharp contrast between bright blue and dark green in the original; at least the RGB version maintains a big contrast between sky and grass.  What's gone wrong?  Let's take a look at the black and white images:

Joe Joe desaturate Joe desat inv
Joe Joe desaturated
(RYB or RGB)
Eoj desaturated
(RYB or RGB)

This looks like an accurate desaturation of Joe.  Except his face seems to blend in more with the sky, and his feet seem to blend in just a bit more with the grass.  This is partly because the color helped tell them apart (yellow on blue, vs gray on gray), but in particular the face has blended in because yellow is actually a brighter color than blue, and looks brighter even though they're the same luminosity, as you see in Joe's black & white.  This is actually our whole problem with the grass not looking dark enough in either color invert above.  Yellow again is a bright color, so it looks brighter than the magenta grass, even though the grass is the lighter shade you see in Eoj's desaturate, and the light red grass looks similar shade and color to the orange, because orange is a brighter color than red (light red is more similar to orange than dark green is to blue).  Perhaps to truly desaturate properly, a program should take into account the brighter or darker hues!

For a quick fix to the orange/red problem, we'll just darken the orange a little and lighten the red to give us an idea.  Also, since we still don't know really whether if either of the RYB or RGB inversions are correct, let's average the two results to see what they look like.  So here are our best guesses at what Eoj looks like:

Joe Joe RYB inv fix Joe RYB inv
Joe Eoj - RYB inv fix Eoj - RYB/RGB inv

Now we could further explore Joe and his inverses by experimenting with different colors (since different colors seem to invert differently in the two systems), and using darker or lighter hues (of the same luminosity), which might give us different results.  But let us move on to actual pictures.  Remember the only way we have to invert any kind of picture is the straight RGB invert of paint, adobe, etc, so we have no choice but to use this.  While it may be incorrect, it can still give us a general idea of what inverted photographs might look like.  After all, it still turns black to white and vice versa.

Here's Joe's friend Kyle.  Kyle is a little more real than Joe because he's a full fictional character in a cool show coming back in 2009 if there's anyone besides me who cares, but he's still fictional at least, so Joe still likes him.  On Kyle's belly button (Kyle's not supposed to have a belly button, so we gave him one) we've put the half of the color spectrum that turns blue when we invert with RGB.  Now all the sky, grass, logo, surrounding Kyle, which are all blue-ish, all turn red-ish, and red and blue for all we've been through are opposites in neither color scheme.  Stranger, Kyle's skin pigment (orangish) all falls to blue, its proper opposite in either color scheme!

Kyle1 >> Kyle Inv
Kyle w/ color
square belly button
Standard PC RGB Invert

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The blue shift is explained by cyan being the opposite of red in RGB, where the logo is very cyan and the dark blue in the sky is not blue at all but dark cyan, otherwise the sky would be yellow (blue's RGB opposite).  It's like everything around Kyle goes into him and the tiny dot of red on his belly button floods the entire sky around.  And while this seems pretty ridiculous in our search for our pure visual inverse (variety in one picture should parallel a variety in the inverse), we can still see that the picture looks pretty darn inverted.  Kyle's hair is white and his face totally alien to us, and there's glowing light where there should be black shadow.  You can invert any picture this way just by pressing ctrl-i in ms-paint or adobe (even if the simple RYB inverse is bizzarely unavailable).

This is just some beginning thoughts on color.  As this short draft becomes longer, I'll discuss the applications of this one color polar extreme to complex emotions, discuss how the whole spectrum of being is related to these two polar necessary extremes (for instance, relating the transitioning from one state of consciousness to another using color to color shifts as an example), and try to apply areas of my other discussions to this as far as it's not redundant.