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Interlaced Colors
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An interlaced color refers to a symbiosis of color and texture. It describes a chaotically homogenous spatial allocation of two (or more) different colors.
Examples of interlaced colors:
Image 1.1/1a:
Interlaced Color Yellow/Blue
Pattern 1
Image 1.1/1b:
Interlaced Color Yellow/Blue
Pattern 2
Image 1.1/1c:
Interlaced Color Yellow/Blue
Pattern 3
Image 1.1/1d:
Interlaced Color Yellow/Blue
Pattern 4
The spatial arrangement is determined by a custom texture map, which is a black and white image that's used to spatially allocate the compound colors of interlaced colors. White areas determine the location of the first compound color, black areas determine the location of the second compound color.
Examples of texture maps:
Image 1.1/2a:
Texture Map
Pattern 1
Image 1.1/2b:
Texture Map
Pattern 2
Image 1.1/2c:
Texture Map
Pattern 3
Image 1.1/2d:
Texture Map
Pattern 4
Interlaced colors are colors that inhabit the Goldilocks zone of spatial adjacency.
When two colors are too far apart, they don't significantly influence each other.
Image 1.1/3a: Red and green dots that are far apart.
Conversely, when two colors are too close and too homogenously spaced, they strongly influence each other to form a retinal color mix.
Image 1.1/3b: One dot that's composed of many directly adjacent, homogenously spaced red and green pixels (Pattern 5). This dots looks yellowish to a normal trichromatic eye, but it's actually a mix of red and green.
The Goldilocks zone of spatial adjacency describes a perfect spatial allocation of two (or more) colors that significantly influence each other without collapsing into their additive color mix. To avoid this "additive collapse", the compound colors need to be in a chaotically homogenous spatial allocation. The homogeneity ensures consistency, so that wherever you look there's roughly the same spatial distribution of colors. And the chaos ensures discriminability, so that colors don't collapse into their additive color mix.
Image 1.1/3c: One dot that's composed of many red and green pixels that are in a chaotically homogenous spatial allocation (Pattern 1). The red and green pixels are far enough apart that they don't collapse into a retinal yellowish color mix, but close enough that they they're linked to each other; i.e. they're "interlaced". When looking directly at this dot, you can still tell that it's colored in a red/green color (mix).
Too homogenous and there will be a collapse.
Image 1.1/3d/1: One dot that's composed of many red and green pixels that are in a "minimally chaotically" homogenous spatial allocation (Pattern 6). The red and green pixels are too close so that they collapse into an additive yellowish mix of red and green, but comparatively fewer small details are lost.
Image 1.1/3d/2:
Texture Map
Pattern 5
Too much chaos and small details will be lost.
Image 1.1/3e/1: One dot that's composed of many red and green pixels that are in a "maximally chaotically" homogenous spatial arrangement (Pattern 6). The red and green pixels are far enough apart that they don't collapse into an additive yellowish mix of red and green, but they introduce so much chaos that small details are lost.
Image 1.1/3e/2:
Texture Map
Pattern 6
If the patterns of the texture map are too big, details will be lost also.
Image 1.1/3f/1: One dot that's composed of many red and green pixels that are in a "weakly/moderately chaotically" homogenous spatial arrangement (Pattern 6). The red and green pixels are far enough apart that they don't collapse into an additive yellowish mix of red and green, but the texture map's patterns are so big that a lot of small details are lost.
Image 1.1/3f/2:
Texture Map
Pattern 2
All these conditions for creating perfectly interlaced colors result in there being the Goldilocks zone of spatial adjacency for interlaced colors. An intelligent spatial distribution of the compound colors of an interlaced color—according to a custom texture map—is important and directly determines the interlaced color's functionality. The two compound colors of an interlaced color have to be close enough that they're linked to each other, yet far enough apart that they don't additively mix.
In their study "Using Patterns to Encode Color Information for Dichromats" Sajadi B. et al. (2011) have already proposed a method for using patterns to encode color information. However, while Sajadi B. et al.'s (2011) method of overlaying each major hue category with a unique pattern may superficially resemble my interlaced colors method, both methods are fundamentally different. Sajadi B. et al.'s (2011) method increases color discriminability by mainly using different patterns for different hue categoires, but my interlaced colors method increases color discriminability by mainly combining two different color spectra in a chaotically homogenous spatial allocation through a custom texture map. With the interlaced colors method color is still the main factor of color discriminability, but with Sajadi B. et al.'s (2011) method the overlaid patterns are the main factor of color discriminability. To my knowledge, the coinage of the term and method "interlaced colors" has first been described here in this article (by Kilian-Roy Lachner) and functionally realized in Custom Color Vision V1.21.
Image 1.2/1: Fig. 7 of the study "Using Patterns to Encode Color Information for Dichromats" by Sajadi B. et al. (2011).
The interlaced colors method can be used to intuitively infer color without creating entirely novel color experiences. This method increases color discriminability through a chaotically homogenous spatial allocation of the colors of two (or more) different custom hue spectra, which overwrites the normal RGB screen colors in real time. It's a method that allows for a considerable retention of small details—depending on the used texture map and compared to Sajadi B. et al.'s (2011) method—as well as a more a intuitive creation and navigation of novel hue/color categories, since color remains the main factor of color discrimination instead of only overlayed patterns.
Contrary to dichoptic colors (i.e. "impossible" color combinations by disrupting the chromatic redundancy of binocular color vision), interlaced colors do not need any more special viewing conditions or equipment to be functionally integrated into your color vision apart from the software (i.e. Custom Color Vision V1.21) that generates them. Regarding dichoptic colors, for example, you need two normally functioning eyes and the ability to cross/parallel view or a VR headset, in addition to special software. Interlaced colors merely presume at least moderately good visual acuity (for preventing additive mixing of more intricate patterns of texture maps) and at a minimum a single functioning eye, in addition to the special software Custom Color Vision V1.21. Thus, interlaced colors are more accessible than dichoptic colors while being similarly functional; although dichoptic colors have a greater potential for maintaing visual details once your dichoptic color vision is trained well enough to be functional.
Other than the slight loss of visual acuity in interlaced colors, both interlaced colors and dichoptic colors resemble each other. Both methods use at leat two color spectra with different colors. While the dichoptic colors method binocularly overlays these two custom color spectra's colors, the interlaced colors method spatially interweaves them. Both of these extraordinary and technologically generated color visions can result in the same functional color vision modification.
Interlaced colors can be used to correct color vision deficiences. Specifically, similar to dichoptic colors, interlaced colors with two compound colors can be used to correct dichromacies towards a functional form of trichromacy. In the following, the dichromacy protanopia is used as an example.
Image 2.1/1: Hue spectrum of normal trichromacy.
Image 2.1/2: "Hue" spectrum of protanopia resp. strong protanomaly.
Image 2.1/3: Vertical arrangement of the two custom color spectra (i.e. custom textures) that allow for correction towards normal trichromacy when using dichoptic colors or interlaced colors. Here, if these red-green dichromatic colors are combined, they generate unique color experiences across the combined spectrum.
Image 2.1/4: Interlacing of the two custom spectra of Image 2.1/3. Here, red-green dichromatic colors are interlaced to generate unique color experiences across the spectrum. The top spectrum represents the first eye's altered color vision, the bottom spectrum respresents the second eye's altered color vision.
Image 2.1/5: Image 2.1/2 and Image 2.1/4 in direct comparison.
Image 2.1/6 shows the hue wheel as it is seen by normal trichromats. Image 2.1/7 shows the same hues, but in interlaced colors, using the two custom color spectra shown in Image 2.1/3.
Although both hue wheels strongly differ in color quality, a trained viewer's color discriminability is identical for Image 2.1/6 and Image 2.1/7. While an individual with the interlaced color vision of Image 2.1/7 would lose some intricate visual details, above a certain threshold their color discriminability is equivalent to that of a normal trichromat with normal color qualities.
Image 2.1/6: Hue wheel with 12 distinct hues (primary, secondary, tertiary).
Image 2.1/7: Hue wheel with 12 distinct interlaced colors.
As a thought experiment to demonstrate the subjective functionality of interlaced colors: For all we know, another person’s subjective experience of red could be either the same as your red, your green, or a color experience completely alien to you—if you could somehow see it. Interlaced colors constitute such an alien color quality. Together with other sensory experiences, this makes the experience of color an incomparable quality. Color tries its best to objectively describe physical attributes, but in reality it necessarily fails at doing so because it’s an entirely subjective experience made up by your brain with limited information.
The subjectivity of qualia permeates every human sensory experience. Each person’s brain essentially is a black box that takes in a range of different stimuli gathered by their senses and converts these abstract signals into what they call their perceived, continuous reality. We can still objectively measure the chemical and electrical signals in their brain, but the moment their brain interprets these signals and hallucinates the illusion of color, we’re neither able to measure that specific subjective experience nor compare its subjective quality to that of another person. The only meaningful and unsurprisingly flawed way to communicate our subjective experience of color is by using other means of communication, like language or pointing at a physical object that evokes this color experience.
In essence, the subjective experience of a color is incomparable between individuals. We can only compare color discriminability, i.e. how well we can differentiate between different wavelengths of light and combinations thereof. Therefore, whether an individual can trichromatically distinguish colors through normal color trichromatic qualities or interlaced dichromatic color qualities is irrelevant, as long as their color discrimininability remains equivalent in both cases. In other words, one color quality is not inherently better than the other as long as the same (or at least a similar) functionality is maintained.
As a more direct visual example in Image 2.1/8, whether the color quality of green is mediated through its "greenness" or through the interlaced color quality's "yellow/blueness" is unimportant, if you can consistently and uniquely distinguish the "green object" as "green".
Image 2.1/8:
Texture Map
Pattern 7
Image 2.1/9: Left semicircle: green color quality (as seen by a normal trichromat) with normal color qualities. Right semicircle: green color quality as seen by an invididual with the interlaced color vision shown in Image 2.1/3, Image 2.1/4 and Image 2.1/7. (Pattern 7).
Therefore, interlaced colors can be used to functionally correct dichromacies (protanopia, deuteranopia, tritanopia) as well as anomalous trichromacies towards normal trichromacy. This functionality is ensured until a certain threshold is reached that's determined by the texture map and the viewed image. Crossing this treshold results in the loss of intricate visual details in favor of color discriminability.
Below you can find the Chaotic Pattern Generator application. It allows you to procedurally generate texture maps for the "interlaced colors support" of Custom Color Vision V1.21. While you can already generate many different texture maps with the Chaotic Pattern Generator application, there's almost an infinite amount of texture maps that you can design for yourself via different methods (e.g. painting by hand, AI generation, procedural generation, etc.). You can be creative and experiment for yourself to create the most functional (or beautiful) texture map for your use case.