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Palette (computing)

Palette (computing) is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Palette (computing) rather than just read about it. In short: In computer graphics, a palette is the set of available colors from which an image can be made. In some systems, the palette is fixed by the hardware design, and in others it is dynamic, typically implemented via a color lookup table (CLUT), a correspondence table in which selected colors from a certain color space's color reproduction range are assigned an index, by which they can be referenced.

Palette (computing) — main illustration
Palette (computing) — illustration

Key takeaways

  • Palette (computing) belongs to computer science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Palette (computing) to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Palette (computing) from memory before moving on to harder problems.

Reference excerpt

In computer graphics, a palette is the set of available colors from which an image can be made. In some systems, the palette is fixed by the hardware design, and in others it is dynamic, typically implemented via a color lookup table (CLUT), a correspondence table in which selected colors from a certain color space's color reproduction range are assigned an index, by which they can be referenced. By referencing the colors via an index, which takes less information than needed to describe the actual colors in the color space, this technique aims to reduce data usage, including processing, transfer bandwidth, RAM usage, and storage. Images in which colors are indicated by references to a CLUT are called indexed color images.

Description As of 2019, the most common image colorspace in graphics cards is the RGB color model with 8 bits per pixel color depth. Using this technique, 8 bits per pixel are used to describe the luminance level in each of the RGB channels, therefore 24 bits fully describe the color of each pixel. The full system palette for such hardware therefore has 224 colors. The objective of the usage of smaller palettes via CLUTs is to lower the number of bits per pixel by reducing the set of possible colors that are to be handled at once (often using adaptive methods). Each possible color is assigned an index, which allows each color to be referenced using less information than needed to fully describe the color. An example is the 256-color palette commonly used in the GIF file format, in which 256 colors to be used to represent an image are selected from the whole 24 bit color space, each being assigned an 8 bit index. This way, while the system can potentially reproduce any color in the RGB color space (as long as the 256 color restriction allows), the storage requirement per pixel is lowered from 24 to 8 bits per pixel.

Master palette

In an application showing many different image thumbnails in a mosaic on screen, the program may not be able to load all the adaptive palettes of every displayed image thumbnail at the same time in the hardware color registers. A solution is to use a unique, common master palette or universal palette, which can be used to display with reasonable accuracy any kind of image. This is done by selecting colors in such way that the master palette comprises a full RGB color space "in miniature", limiting the possible levels that the red, green, and blue components may have. This kind of arrangement is sometimes referred to as a uniform palette. The normal human eye has sensibility to the three primary colors in different degrees: the more to the green, the less to the blue. So RGB arrangements can take advantage of this by assigning more levels for the green component and fewer to the blue. A master palette built this way can be filled with up to 8R×8G×4B = 256 colors, but this does not leave space in the palette for reserved colors, color indices that the program could use for special purposes. It is more general to use only 6R×6G×6B = 216 (as in the Web colors case), 6R×8G×5B = 240 or 6R×7G×6B = 252, which leaves room for some reserved colors. Then, when loading the mosaic of image thumbnails (or other heterogeneous images), the program simply maps every original indexed color pixel to its most approximated in the master palette (after dumping this into the hardware color registers), and writes the result in the video buffer. Here is a sample of a simple mosaic of the four image thumbnails using a master palette of 240 RGB arranged colors plus 16 additional intermediate shades of gray; all images are put together without a significant loss of color accuracy:

Adaptive palette When using indexed color techniques, real life images are represented with better fidelity to the truecolor original one by using adaptive palettes (sometimes termed adaptative palettes), in which the colors are selected or quantized through some algorithm directly from the original image (by picking the most frequent colors). This way, and with further dithering, the indexed color image can nearly match the original. But this creates a heavy dependence between the image pixels and its adaptive palette. Assuming a limited 8-bit depth graphic display, it is necessary to load a given image's adaptive palette into the color hardware registers prior to loading the image surface itself into the frame buffer. To display different images with different adaptive palettes, they must be loaded one by one, as in a slideshow. Here are samples of four different indexed color images with color patches to show their respective (and largely incompatible) adaptive palettes:

Transparency in palettes

… excerpt ends here. Continue reading the full article.

Illustrations

Palette (computing) illustration
Palette (computing) illustration
Palette (computing) illustration
Palette (computing) illustration
Palette (computing) illustration

Worked examples

Example 1 — a first encounter with Palette (computing)

Start with the simplest possible case. Write down what Palette (computing) claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Palette (computing) before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Palette (computing) ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Palette (computing)

In research
Palette (computing) appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Palette (computing) in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Palette (computing) is common in secondary-school and first-year university syllabi. It links to neighbouring topics Color depths, Computer graphics data structures, Computer output devices, so understanding it makes those chapters shorter.
In everyday life
Look for Palette (computing) outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Palette (computing) in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Palette (computing) means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Palette (computing) out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Palette (computing) in simple terms?

In computer graphics, a palette is the set of available colors from which an image can be made. In some systems, the palette is fixed by the hardware design, and in others it is dynamic, typically implemented via a color lookup table (CLUT), a correspondence table in which selected colors from a ce…

Why does Palette (computing) matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Palette (computing)?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Palette (computing).

Tags

  • Color depths
  • Computer graphics data structures
  • Computer output devices

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