ind2rgb
Convert indexed image to RGB image
Syntax
Description
Examples
Convert Indexed Image to RGB
Read the first image in a sample indexed image file.
[A,map] = imread("corn.tif"); whos A map
Name Size Bytes Class Attributes A 415x312 129480 uint8 map 256x3 6144 double
The indexed image A
is a 415-by-312 matrix of type uint8
, and the colormap map
is a 256-by-3 matrix of type double
. The dimensions of map
indicate that the indexed image contains up to 256 colors.
Display the image.
imshow(A,map)
Convert the indexed image to an RGB image. The result is a 415-by-312-by-3 array of type double
.
RGB = ind2rgb(A,map);
Check that the values of the RGB
image are in the range [0, 1].
[minVal,maxVal] = bounds(RGB(:))
minVal = 0.0078
maxVal = 0.9765
Input Arguments
X
— Indexed image
m-by-n matrix of integers
Indexed image, specified as an m-by-n matrix of integers.
If you specify
X
as an array of integer data type, then the value 0 corresponds to the first color in the colormapmap
. For a colormap containing c colors, values of imageX
are clipped to the range [0, c-1].If you specify
X
as an array of data typesingle
ordouble
, then the value 1 corresponds to the first color in the colormap. For a colormap containing c colors, values of imageX
are clipped to the range [1, c].
Data Types: single
| double
| uint8
| uint16
map
— Colormap
c-by-3 matrix
Colormap associated with indexed image X
, specified as a
c-by-3 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.
Data Types: double
Output Arguments
RGB
— RGB image
m-by-n-by-3 numeric array
RGB image, returned as an m-by-n-by-3 numeric array with values in the range [0, 1].
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™.
The ind2rgb
function
fully supports GPU arrays. To run the function on a GPU, specify the input data as a gpuArray
(Parallel Computing Toolbox). 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 before R2006a
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