cmap2gray
Syntax
Description
Examples
Convert RGB Colormap to Grayscale Colormap Using cmap2gray
Load an indexed image with its colormap into the workspace. The load
command returns a structure containing the image data and the colormap. View the image.
indImage = load('clown.mat');
figure
imshow(indImage.X,indImage.map)
Convert the RGB colormap that came with the image into a grayscale colormap.
newmap = cmap2gray(indImage.map);
Display the image with the grayscale colormap.
figure; imshow(indImage.X,newmap)
Input Arguments
map
— RGB colormap
c-by-3 numeric matrix
RGB colormap, specified as a c-by-3 numeric matrix with values in
the range [0, 1]. Each row of map
is a three-element RGB triplet
that specifies the red, green, and blue components of a single color of the
colormap.
If you have Parallel Computing Toolbox™ installed, map
can also be a
gpuArray
.
Data Types: double
Output Arguments
newmap
— Grayscale colormap
c-by-3 numeric matrix
Grayscale colormap, returned as a c-by-3 numeric matrix with
values in the range [0, 1]. The three columns of newmap
are
identical, so that each row specifies a single intensity value.
If you have Parallel Computing Toolbox installed, then newmap
can also be a gpuArray.
Data Types: double
Extended Capabilities
C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.
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 Run MATLAB Functions on a GPU (Parallel Computing Toolbox).
Distributed Arrays
Partition large arrays across the combined memory of your cluster using Parallel Computing Toolbox™.
This function fully supports distributed arrays. For more information, see Run MATLAB Functions with Distributed Arrays (Parallel Computing Toolbox).
Version History
Introduced in R2020b
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