Resize image
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Syntax
B = imresize(A,scale)
B = imresize(A,[numrows numcols])
[Y,newmap]= imresize(X,map,___)
___ = imresize(___,method)
___ = imresize(___,Name,Value)
Description
example
B = imresize(A,scale) returns image B that is scale times the size of image A. The input image A can be a grayscale, RGB, binary, or categorical image.
If A has more than two dimensions, then imresize only resizes the first two dimensions. If scale is between 0 and 1, then B is smaller than A. If scale is greater than 1, then B is larger than A. By default, imresize uses bicubic interpolation.
example
B = imresize(A,[numrows numcols]) returns image B that has the number of rows and columns specified by the two-element vector [numrows numcols].
example
[Y,newmap]= imresize(X,map,___) resizes the indexed image X where map is the colormap associated with the image.
example
___ = imresize(___,method) specifies the interpolation method used.
___ = imresize(___,Name,Value) returns the resized image where name-value arguments control various aspects of the resizing operation. Specify name-value arguments after all other input arguments.
Examples
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Shrink Image By Factor of Two Using Default Interpolation Method
Open Live Script
Load image into the workspace.
I = imread('ngc6543a.jpg');Shrink the image by a factor of two.
J = imresize(I, 0.5);
Display the original image and the resized image.
figure, imshow(I), figure, imshow(J)
Shrink Image Using Nearest-Neighbor Interpolation
Open Live Script
Load an image into the workspace.
I = imread('ngc6543a.jpg');Shrink the image to 40% of the original size using nearest-neighbor interpolation. This is the fastest method, but it has the lowest quality.
J = imresize(I,0.4,'nearest');Display the original image and the resized image.
imshow(I)title('Original Image')
imshow(J)title('Resized Image Using Nearest Neighbor Interpolation')
Resize RGB Image Specifying Size of Output Image
Open Live Script
Read an RGB image into the workspace.
RGB = imread('peppers.png');Resize the RGB image to have 64 rows. imresize calculates the number of columns automatically.
RGB2 = imresize(RGB,[64 NaN]);
Get the size of the resized image.
sz = size(RGB2)
sz = 1×3 64 86 3Display the original image and the resized image.
imshow(RGB)title("Original Image")
imshow(RGB2)title("Resized Image with 64 Rows")
Resize Indexed Image
Open Live Script
Read an indexed image into the workspace.
[X,map] = imread("corn.tif");Increase the size of the indexed image by 50%.
[Y,newmap] = imresize(X,map,1.5);
Display the original image and the resized image.
imshow(X,map)title("Original Indexed Image and Colormap")
imshow(Y,newmap)title("Resized Image and Optimized Colormap")
Input Arguments
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A — Image to be resized
numeric array | logical array | categorical array
Image to be resized, specified as a numeric array, logical array, or categorical array of any dimension. Input must be nonsparse, and numeric input must be real.
Data Types: single | double | int8 | int16 | int32 | uint8 | uint16 | uint32 | logical | categorical
scale — Resize factor
positive number
Resize factor, specified as a positive number. imresize applies the same scale factor to the row and column dimensions. To apply a different resize factor to each dimension, use the Scale name-value argument.
If you specify a resize factor that does not result in integer-length image dimensions, then imresize follows the resizing operation with a call to the ceil function. In other words, the output image has ceil(scale*size(A,1)) rows and ceil(scale*size(A,2)) columns.
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64
[numrows numcols] — Row and column dimensions of output image
two-element vector of positive numbers
Row and column dimensions of output image, specified as a two-element vector of positive numbers. You can specify the value NaN for either numrows or numcols. In this case, imresize calculates the number of rows or columns for that dimension automatically, preserving the aspect ratio of the image.
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64
X — Indexed image to be resized
real, nonsparse numeric array
Indexed image to be resized, specified as a real, nonsparse numeric array of positive integers.
Data Types: double | uint8 | uint16
map — Colormap associated with indexed image
c-by-3 numeric matrix
Colormap associated with indexed image X, specified 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.
Data Types: double
method — Interpolation method
character vector | string scalar | two-element cell array
Interpolation method, specified as a character vector, string scalar, or two-element cell array. The default value for numeric and logical images is "bicubic". The default value for categorical images is "nearest". Categorical images only support the values "nearest" and "box".
When method is a character vector or string scalar, it identifies a particular method or named interpolation kernel, listed in the following table.
| Method | Description |
|---|---|
| Nearest-neighbor interpolation; the output pixel is assigned the value of the pixel that the point falls within. No other pixels are considered. |
| Bilinear interpolation; the output pixel value is a weighted average of pixels in the nearest 2-by-2 neighborhood. |
| Bicubic interpolation; the output pixel value is a weighted average of pixels in the nearest 4-by-4 neighborhood. Note Bicubic interpolation can produce pixel values outside the original range. |
| Interpolation Kernel | Description |
"box" | Box-shaped kernel |
"triangle" | Triangular kernel (equivalent to "bilinear") |
"cubic" | Cubic kernel (equivalent to "bicubic") |
"lanczos2" | Lanczos-2 kernel |
"lanczos3" | Lanczos-3 kernel |
When method is a two-element cell array, it defines a custom interpolation kernel. The cell array has the form {f,w}, where f is a function handle for a custom interpolation kernel and w is the width of the custom kernel. f(x) must be zero outside the interval -w/2 <= x < w/2. The function handle f can be called with a scalar or a vector input. For user-specified interpolation kernels, the output image can have some values slightly outside the range of pixel values in the input image.
For more information about the built-in and custom interpolation kernels, see Create and Compare Resizing Interpolation Kernels.
Data Types: char | string | cell
Name-Value Arguments
Specify optional pairs of arguments as Name1=Value1,...,NameN=ValueN, where Name is the argument name and Value is the corresponding value. Name-value arguments must appear after other arguments, but the order of the pairs does not matter.
Example: B = imresize(A,0.5,Antialiasing=false) does not perform antialiasing when shrinking an image.
Before R2021a, use commas to separate each name and value, and enclose Name in quotes.
Example: B = imresize(A,0.5,"Antialiasing",false) does not perform antialiasing when shrinking an image.
Antialiasing — Perform antialiasing when shrinking an image
true | false
Perform antialiasing when shrinking an image, specified as true or false.
If the interpolation method is
"nearest", then the default value ofAntialiasingisfalse.If the interpolation
methodis"box"and the input image is categorical, then the default value ofAntialiasingisfalse.For all other interpolation methods, the default value is
true.
Data Types: logical
Colormap — Return optimized colormap
"optimized" (default) | "original"
Return optimized or original colormap for indexed image, specified as one of the following values.
| Value | Description |
|---|---|
"original" | The output colormap newmap is the same as the input colormap map. |
"optimized" | imresize returns a new optimized colormap. |
The Colormap argument is valid only when resizing indexed images.
Data Types: char | string
Dither — Perform color dithering
true (default) | false
Perform color dithering, specified as true or false. In dithering, you apply a form of noise to the image to randomize quantization error and prevent large-scale patterns.
The Dither argument is valid only when resizing indexed images.
Data Types: logical
Method — Interpolation method
character vector | string scalar | cell array
Interpolation method, specified as a character vector, string scalar, or two-element cell array. For details, see method.
Data Types: char | string | cell
OutputSize — Size of output image
two-element vector of positive numbers
Size of the output image, specified as a two-element vector of positive numbers. For details, see [numrows numcols].
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64
Scale — Resize scale factor
positive number | two-element vector of positive numbers
Resize scale factor, specified as a positive number or two-element vector of positive numbers. If you specify a scalar, then imresize applies the same scale factor to the row and column dimensions. If you specify a two-element vector, then imresize applies a different scale value to each dimension.
If you specify a resize scale factor that does not result in integer-length image dimensions, then imresize follows the resizing operation with a call to the ceil function. In other words, the output image has ceil(Scale(1)*size(A,1)) rows and ceil(Scale(2)*size(A,2)) columns.
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64
Output Arguments
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B — Resized image
numeric array | logical array | categorical array
Resized image, returned as a numeric, logical, or categorical array of the same data type as the input image, A.
Y — Resized indexed image
numeric array
Resized indexed image, returned as a numeric array of the same data type as the input indexed image, X.
newmap — Colormap of resized indexed image
m-by-3 numeric matrix
Colormap of the resized indexed image Y, returned as an m-by-3 numeric matrix. By default, imresize returns a new, optimized colormap with the resized image. To return a colormap that is the same as the original colormap, use the Colormap name-value argument.
Extended Capabilities
C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.
Usage notes and limitations:
Syntaxes that support indexed images are not supported, including the name-value arguments
ColormapandDither.Custom interpolation kernels are not supported.
All name-value arguments must be compile-time constants.
GPU Code Generation
Generate CUDA® code for NVIDIA® GPUs using GPU Coder™.
Usage notes and limitations:
ColormapandDithername-value arguments are not supported.Indexed images are not supported.
Custom interpolation kernels are not supported.
All name-value pairs must be compile-time constants.
For certain interpolation kernels, there can be a small numerical mismatch between the results in MATLAB® and the generated code.
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™.
Usage notes and limitations:
gpuArrayinput with more than 227 elements is not supported.gpuArrayinput must be non-sparse.gpuArrayinput with underlying typecategoricalis not supported.Indexed images are not supported on a GPU.
If you use bicubic interpolation, the output image can have some values slightly outside the range of pixel values in the input image.
There is a slight numerical difference between the results of
imresizeon a CPU and a GPU. These differences occur on the right and bottom borders of the image and are barely noticeable to the naked eye.
For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).
Version History
Introduced before R2006a
expand all
R2019a: Supports categorical images
The imresize function now supports categorical images.
See Also
imresize3 (Image Processing Toolbox) | interp2
Topics
- Working with Image Types in MATLAB
- Create and Compare Resizing Interpolation Kernels
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