Skip to main content

Notes on Color #3: Color Spaces

The first time I heard of the term "color space" was probably from some article about display color gamut/calibration. I learned that it is important for a display to achieve at least 100% sRGB, for digital painting or image processing. Well I didn't know what exactly "s" means here, but I got a feeling that it has something to do with the RGB values in HTML color codes.

A few color spaces
Source: Wikipedia CC BY-SA 3.0


The diagram could be very confusing. I had a few questions, which I think I can answer today:

Why does it look like a weird 2d shape, instead of a 3d volume?
It is a 2d shape, which is a slice of the 3d space at a constant luminance.
More specifically, this is a sliced xy space at a specific value of Y.

Why does the sRGB color space appear as a triangle?
The sRGB color space is generated by 3 primary colors, which corresponds to the 3 vertices of the triangle. Moreover, for any 2 colors, all available colors obtained by mixing these 2 colors (with different ratios) corresponds to all points on the line segment that connects the 2 points.

Assuming RGB values, (1, 1, 0) may be obtained by mixing (1, 0, 0) and (0, 1, 0). However they are not on a line.
The idea is that luminance and chromaticity may be examined independently. (1, 1, 0) would have the same chromaticity as (0.5, 0.5, 0), which is on the line segment connecting (1, 0, 0) and (0, 1, 0).
However, note that (0.5, 0.5, 0) is not necessarily the middle point on the xy diagram. Simliarly, the white point is not necessarily the gravicity center of the triangle.


This wiki page lists and compares a number of color spaces. Here are my notes:

CAM - Color Appearance Model, which describes human perceiption of colors. These models could be useful for choosing colors. Difficult to compute. Examples: CAM16, Oklab, CIECAM02, CIELAB.

UCS - Uniform Color Space, in which the distance between two color points reflects the color difference perceived by human. These models could be useful for generating gradients. Difficult to compute. Examples: CAM16-UCS, OSA-UCS.

RGB - Generated with 3 primary colors. It is widely used for display devices and media encoding. The linear version (without gamma correction/encoding) is also useful for mixing colors (lights) and rendering. Easy to compute. Examples: sRGB, Adobe RGB.

HSV, HSL, HSI, HSY - Cylindrical transformations of RGB. Widely used for historical reasons. Easy to compuate but very inaccurate. 

Finally, I found the following videos very helpful:
Labels:

Comments

Post a Comment

Popular posts from this blog

Determine Perspective Lines With Off-page Vanishing Point

In perspective drawing, a vanishing point represents a group of parallel lines, in other words, a direction. For any point on the paper, if we want a line towards the same direction (in the 3d space), we simply draw a line through it and the vanishing point. But sometimes the vanishing point is too far away, such that it is outside the paper/canvas. In this example, we have a point P and two perspective lines L1 and L2. The vanishing point VP is naturally the intersection of L1 and L2. The task is to draw a line through P and VP, without having VP on the paper. I am aware of a few traditional solutions: 1. Use extra pieces of paper such that we can extend L1 and L2 until we see VP. 2. Draw everything in a smaller scale, such that we can see both P and VP on the paper. Draw the line and scale everything back. 3. Draw a perspective grid using the Brewer Method. #1 and #2 might be quite practical. #3 may not guarantee a solution, unless we can measure distances/p...
3 comments
Read More »

Qubes OS: First Impressions

A few days ago, while browsing security topics online, Qubes OS surfaced—whether via YouTube recommendations or search results, I can't recall precisely. Intrigued by its unique approach to security through compartmentalization, I delved into the documentation and watched some demos. My interest was piqued enough that I felt compelled to install it and give it a try firsthand. My overall first impression of Qubes OS is highly positive. Had I discovered it earlier, I might have reconsidered starting my hardware password manager project. Conceptually, Qubes OS is not much different from running a bunch of virtual machines simultaneously. However, its brilliance lies in the seamless desktop integration and the well-designed template system, making it far more user-friendly than a manual VM setup. I was particularly impressed by the concept of disposable VMs for temporary tasks and the clear separation of critical functions like networking (sys-net) and USB handling (sys-usb) into the...
Post a Comment
Read More »

Exploring Immutable Distros and Declarative Management

My current server setup, based on Debian Stable and Docker, has served me reliably for years. It's stable, familiar, and gets the job done. However, an intriguing article I revisited recently about Fedora CoreOS, rpm-ostree, and OSTree native containers sparked my curiosity and sent me down a rabbit hole exploring alternative approaches to system management. Could there be a better way? Core Goals & Requirements Before diving into new technologies, I wanted to define what "better" means for my use case: The base operating system must update automatically and reliably. Hosted services (applications) should be updatable either automatically or manually, depending on the service. Configuration and data files need to be easy to modify, and crucially, automatically tracked and backed up. Current Setup: Debian Stable + Docker My current infrastructure consists of several servers, all running Debian Stable. System Updates are andled automatically via unattended-upgrades. Se...
Post a Comment
Read More »