paletteindexed

Palette-indexed refers to a color representation mode commonly used in computer graphics and image processing. In this mode the image data stores, for each pixel, an index that refers to a separate list of colors known as a color palette or colormap. The palette itself contains a limited set of color values, typically 256 or fewer. The pixel data thus requires only one byte per pixel when 256 colors are used, which saves memory and can speed up certain operations such as image loading and manipulation.

The palette-indexed model originated with early graphical systems and remains the backbone of many traditional file formats, such as GIF, old PC BMP, Netpbm (P5, P4), and X window system window bitmaps. It also underlies indexed color support in PNG through the tRNS and PLTE chunks. In these contexts the palette may be either fixed by the file format specification or defined by the creator of the image. Because the palette is stored separately from the pixel data, it can be shared among several images or reused to change the coloration of an image without altering its pixel grid.

A key advantage of palette-indexed images is the reduced size of bitmap data compared to true-color formats that store three or four bytes per pixel. This makes palette-indexed images attractive for old systems with limited storage, for icon graphics, or for applications where color fidelity is not critical. However, because the palette can hold only a limited number of colors, images with complex textures or gradients may suffer from banding or poor color representation. Selecting an optimal palette, sometimes using dithering techniques, is a common issue that designers must address.

Modern graphics standards have largely moved toward true-color (8‑bit per channel or higher) systems, but palette-indexed formats retain niche usage. They are still supported in many libraries and are useful in scenarios such as embedded devices, retro-style games, or when a small file footprint is a priority. Their simplicity also aids in educational contexts, where students can learn about color quantization, palette generation, and the trade‑offs between color depth and file size.