gray2ind

Convert grayscale or binary image to indexed image

Syntax

[X,cmap] = gray2ind(I,c)

[X,cmap] = gray2ind(BW,c)

Description

[X,cmap] = gray2ind(I,c) converts the grayscale image I to an indexed image X with colormap cmap with c colors.

[X,cmap] = gray2ind(BW,c) converts the binary image BW to an indexed image.

Examples

Convert Grayscale Image to Indexed Image

Read grayscale image into the workspace.

I = imread('cameraman.tif');

Convert the image to an indexed image using gray2ind. This example creates an indexed image with 16 indices.

[X, map] = gray2ind(I, 16);

Display the indexed image.

imshow(X, map);

Input Arguments

I — Grayscale image

numeric array

Grayscale image, specified as a numeric array of any dimension.

Data Types: single | double | int16 | uint8 | uint16

BW — Binary image

numeric array

Binary image, specified as a numeric array of any dimension.

Data Types: logical

c — Number of colormap colors

positive integer

Number of colormap colors, specified as a positive integer between 1 and 65536.

• If the input image is grayscale, then the default value of c is 64.

• If the input image is binary, then the default value of c is 2.

Output Arguments

X — Indexed image

numeric array

Indexed image, returned as a numeric array of the same dimensionality as the input grayscale or binary image. If the colormap length is less than or equal to 256, then the class of the output image is uint8 ; otherwise it is uint16.

Data Types: uint8 | uint16

cmap — Colormap

c-by-3 numeric matrix

Colormap associated with indexed image X, returned as a c-by-3 numeric matrix with values in the range [0, 1]. Each row is a three-element RGB triplet that specifies the red, green, and blue components of a single color of the colormap. The colormap is equivalent to gray(c).

Data Types: double

Extended Capabilities

Thread-Based Environment

Run code in the background using MATLAB® backgroundPool or accelerate code with Parallel Computing Toolbox™ ThreadPool.

This function fully supports thread-based environments. For more information, see Run MATLAB Functions in Thread-Based Environment.

GPU Arrays

Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.

This function fully supports GPU arrays. For more information, see Image Processing on a GPU.

Version History

Introduced before R2006a

R2022b: Support for GPU acceleration

gray2ind now supports GPU acceleration (requires Parallel Computing Toolbox™).

R2021b: Support for thread-based environments

gray2ind now supports thread-based environments.