A case of visual aesthetics: Why is the monochrome image superior to the color image?

Last Saturday (July 18, 2026) I posted, Some notes on AI and “fine art” imagery, which included these two images, remarking that the first seemed superior to the second:

But I didn’t ask why it is superior. Now I’m asking: Why?

FWIW, ChatGPT produced the first image based on my prompt. I forget the exact working of the prompt, but it was simple. After uploaded a long document about virtual reading I directed it to create an image for the cover of that document. That color image is what it gave me. I liked the form, but found the color distracting, so I asked it to render the image as a Renaissance engraving, resulting in the first image.

To investigate the question I used Photoshop to alter the color version. For this one I reduced the level of saturation:

Here I rendered the image in monochrome blue:

Finally, monochrome grayscale:

All three strike me as being superior to the original color image. The de-saturated version still has color in it, but the color is not so prominent. The monochrome blue has color information, obviously, but only one hue, so there is no contrast between hues. Finally, the grayscale image has no color information at all. Of the two monochrome images, is one better than the other? At the moment I like the blue better than the grayscale, but I’m not sure it matters much.

But I like the engraving rendition better than either of those. Why? It has a much richer texture. Without bothering to has things out, let’s posit that as part of the reason for the superiority of that version over the original color version.

But that doesn’t explain why the other three are superior to the original. What they have in common is less color information. There’s no color information in the grayscale image and the range of color information in the other two is reduced, drastically so in the blue image.

Why should that matter? Let me speculate. The vision system handles brightness differently than it does hue. Luminance is picked up by so-called rods in the retina while color is picked up by cones. To my eye the color information is just there in the color image. It forms no interesting pattern one its own and it doesn’t seem to be interacting with brightness in any way. It adds nothing but color itself.

Let’s speculate a bit farther. Some years ago Mark Changizi published The Vision Revolution (2009). He argued that the biological purpose of color vision is to allow us to read one another’s emotions more accurately based on gradations in skin color. I find his arguments persuasive. Now, while that may be the primary function of color vision, color vision obviously is not confined to how we see other humans. We use it generally in the world.

Now, let’s look at that image. The only recognizable object in it is that book, and it has very little color in it. The rest of it is just spots, lines and swirls that doesn’t look like anything. But maybe it looks a little like veins beneath the skin, not much, but perhaps enough to “invite” the color system to look for emotional resonance, and fail. It’s that invitation-and-failure that makes the color information, not simply irrelevant, but actively distracting.

Do I believe this? Yes and no. It’s speculation. I just made it up. To move from there to belief I’ve have to come up with a way of actually investigating the question, which is more than I’m in a position to do at the moment.

Mulling. Sometimes monochrome even looks … better in some sense… on human faces. 🤷

— Mark Changizi (@MarkChangizi) July 20, 2026

Pier in fog over the Hudson

Color games

The spirit of El Greco over Manhattan yesterday evening

Matisse pincushion [stars]

Some quick notes on color in a photo

This is more or less how the scene appeared to me when I shot it:

Notice that the only things that are in focus are the large weeds in the foreground. Everything else is a bit soft. I’m fine with that.

Here’s how the image looked when it came out of the camera:

The lower half is dark and muddy. Something needs to be done. I began by equalizing the pixels. Don’t worry about just what that means, it’s a single menu option in Photoshop: Equalize.

I like that, I like it a lot. Though it’s not what my eyes saw – the color’s certainly off – it clarifies what’s happening with the light. I’m looking south and the sunlight’s coming in low from the left. Everything below the elevated roadway is in shadow – notice the dark line to the right of center, ‘cutting’ through the vegetation. Everything below the line is in the shade; everything above the line gets the sunlight.

In this image I de-saturated the blue a bit:

The weeds in the foreground are now much more visible than they are in the first picture. Still, the color’s a bit unnatural, though if I were painting the image, I might well go for the unnatural color.

To produce this image I simply converted the equalized image to grey scale:

Finally, in this image I took the equalized image and ramped up the saturation for reds and yellows:

The neural basis of color perception

As an aspiring brain scientist, my project was to discover the brain implementation of Opponent Colors Theory, the accepted explanation of color appearance. It took 20 yrs of trying (& failing) to find the corresponding neurophysiology, to realize the theory is wrong #color 1/8 https://t.co/vYPvM7y2Cy

— Bevil Conway (@BevilConway) July 7, 2023

Central Park Make-Over

Color play for the new year

Three versions of a lily

Across 110 languages, people can describe warm colors (🟡🔴) faster than cool ones (🔵🟢). Why?

A universal: across 110 languages, people can describe warm colors (🟡🔴) faster than cool ones (🔵🟢). Why?

We create names for what we need to talk about! Warm colors are more likely to describe objects (🐅🧍‍♂️) we want to point out, cool ones describe backgrounds (🌳🌊) 1/3 pic.twitter.com/wTj727zwqC

— Ethan Mollick (@emollick) June 4, 2022

Just looking at Ingrid Sunderberg's color thesaurus you can see how many colors are simply the names of objects of that color - we label what we want to discuss. https://t.co/pKnNBCxJ1A

Here’s the first paper: https://t.co/McCni8nfEh

And the second: https://t.co/CQMjyVJ6AO 3/3 pic.twitter.com/khtO10tgO3

— Ethan Mollick (@emollick) June 4, 2022

Update on Color Terms: Nature or Nuture?

More on color terms [1.27.22]:

 

 

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Thinking about this again so I'm bumping this to the top. It's from December 2012.

Color vision, from genetics through neuropsychology to color terms, is one of the most intensely investigated topics in cognitive science. The subject is interesting for two reasons:

1. as psychological phenomena go, it's relatively simple, and accessible to investigation through a variety of methods, and
2. in particular, it can be studied cross-culturally and thus shed light on the nature-nurture question.

Mark Changizi has recently argued the color vision has evolved for the purpose of allowing us to obtain clues about a person's health and state of mind from changes in skin color, blushing, bruising, and the like. He's stated this idea at some length in the first chapter of The Vision Revolution (BenBella Books, 2009, pp. 5-48). Folks have been discussing this idea at some length over at Crooked Timber.

In thinking through that discussion I formulated this question and sent it to Changizi: Question: Lots of languages have rather impoverished systems of color terms. Would folks speaking a language that lacked a term for green thereby have more fine-grained perception of greens? He didn't have an answer but indicated that people are working on that kind of issue. He sent me reprints of two papers that are indeed relevant. 

Color terminology seems subject to constraints that are universal but, at the same time, differences in color naming across cultures does seem to cause differences in color perception. How do you like them apples? Both universal and different at the same time.

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Paul Kay and Terry Regier. Language, thought and color: recent developments. TRENDS in Cognitive Sciences Vol.10 No.2 February 2006, pp. 51-54

Here's how Kay and Regier state matters as they existed, say, a quarter of a century ago:

Color naming varies across languages; however, it has long been held that this variation is constrained. Berlin and Kay [1] found that color categories in 20 languages were organized around universal ‘focal colors’ – those colors corresponding principally to the best examples of English ‘black’, ‘white’, ‘red’, ‘yellow’, ‘green’ and ‘blue’. Moreover, a classic set of studies by Eleanor Rosch found that these focal colors were also remembered more accurately than other colors, across speakers of languages with different color naming systems (e.g. [2]). Focal colors seemed to constitute a universal cognitive basis for both color language and color memory.

Research conducted in the last decade or so has called those conclusions into question. Kay and Regier present and discuss this work and offer this summary:

The debate over color naming and cognition can be clarified by discarding the traditional ‘universals versus relativity’ framing, which collapses important distinctions. There are universal constraints on color naming, but at the same time, differences in color naming across languages cause differences in color cognition and/or perception. The source of the universal constraints is not firmly established. However, it appears that it can be said that nature proposes and nurture disposes. Finally, ‘categorical perception’ of color might well be perception sensu stricto, but the jury is still out.

The key proposition is that "differences in color naming across languages cause differences in color cognition and/or perception."

* * * * *

Paul Kay and Terry Regier, Resolving the question of color naming universals, PNAS, vol. 100, no. 15, July 22, 2003, pp. 9085-9089.

Abstract:

The existence of cross-linguistic universals in color naming is currently contested. Early empirical studies, based principally on languages of industrialized societies, suggested that all languages may draw on a universally shared repertoire of color categories. Recent work, in contrast, based on languages from nonindustrialized societies, has suggested that color categories may not be universal. No comprehensive objective tests have yet been conducted to resolve this issue. We conduct such tests on color naming data from languages of both industrialized and nonindustrialized societies and show that strong universal tendencies in color naming exist across both sorts of language.

From the methodology discussion:

The central empirical focus of our study was the color naming data of the Word Color Survey (WCS). The WCS was undertaken in response to the above-mentioned shortcomings of the BK [Berlin and Kay] data (1): it has collected color naming data in situ from 110 unwritten languages spoken in small-scale, nonindustrialized societies, from an average of 24 native speakers per language (mode: 25 speakers), insofar as possible monolinguals. Speakers were asked to name each of 330 color chips produced by the Munsell Color Company (New Windsor, NY), representing 40 gradations of hue at eight levels of value (lightness) and maximal available chroma (saturation), plus 10 neutral (black-gray-white) chips at 10 levels of value. Chips were presented in a fixed random order for naming. The array of all color chips is shown in Fig. 1. (The actual stimulus colors may not be faithfully represented there.) In addition, each speaker was asked to indicate the best example(s) of each of his or her basic color terms. The original BK study used a color array that was nearly identical to this, except that it lacked the lightest neutral chip. The languages investigated in the WCS and BK are listed in Tables 1 and 2.

The concluding paragraph:

The application of statistical tests to the color naming data of the WCS has established three points: (i) there are clear cross-linguistic statistical tendencies for named color categories to cluster at certain privileged points in perceptual color space; (ii) these privileged points are similar for the unwritten languages of nonindustrialized communities and the written languages of industrialized societies; and (iii) these privileged points tend to lie near, although not always at, those colors named red, yellow, green, blue, purple, brown, orange, pink, black, white, and gray in English.

Theories of color among blind people

1. Result: Blind adults show low agreement on the common color of objects (e.g. strawberry, stop sign = red). But blind & sighted make the same predictions for novel object color, based on knowing kind (natural/artifact) & its relation to color (e.g. color important to function) pic.twitter.com/qXDEDIk65n

— Judy Kim⁷ (@joodykeem) August 16, 2021

3. We argue: people develop causal-explanatory “intuitive theories” of color regardless of color experience. These theory-like understandings are, perhaps counterintuitively, *more* likely to be acquired than arbitrary associations (e.g., which color goes with which object).

— Judy Kim⁷ (@joodykeem) August 16, 2021

5. Exactly how color info is acquired is an open Q. Language is part of the answer, ofc. But importantly, to the extent that lang communicates about color, the “why” is acquired even when the “what” is not. So the key ? is the role of language in the development of these theories

— Judy Kim⁷ (@joodykeem) August 16, 2021

7. Another future direction is the role of pragmatics (thinking about what someone w/ different experience would say, e.g., a blind person thinking about sighted or vice versa).

Also, a challenge for AI: whether “understanding” & not just that strawberries = red can be learned

— Judy Kim⁷ (@joodykeem) August 16, 2021

There's more to the tweet stream, but perhaps it would be more direct simply to download the whole paper. That's what I'm going to do.

Hot pink smooch

Blue green yellow orange red

Phases of the moon [Photoshop]

The problematic of color [eye and camera]

This is how the image came out of the camera, more or less:

That's not what I saw when I took the picture. Not those colors.

Now I've calibrated the image so that the face of the largest building is not pink:

Good enough. But where's that green come from? I'm certain I didn't see that.

This is what I settled on:

Still, where'd that pink come from? Was it really there?

Here we see pink clouds:

Is the pink on the face of that building a reflection from the clouds, something registered by my camera, but not my eye?

This, of course, solves the problem, but at a price:

For a more detailed discussion of color and color photography, see Color the Subject.