imabsdiff

Absolute difference of two images

Syntax

Z = imabsdiff(X,Y)

Description

Z = imabsdiff(X,Y) subtracts each element in array Y from the corresponding element in array X and returns the absolute difference in the corresponding element of the output array Z.

Examples

Display Absolute Difference between Filtered image and Original

Read image into workspace.

I = imread('cameraman.tif');

Filter the image.

J = uint8(filter2(fspecial('gaussian'), I));

Calculate the absolute difference of the two images.

K = imabsdiff(I,J);

Display the absolute difference image.

figure
imshow(K,[])

Input Arguments

X — Input image

numeric array

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

Example: x = imread('cameraman.tif');

Data Types: single | double | int8 | int16 | int32 | uint8 | uint16 | uint32 | logical

Y — Input image

numeric array

Input image, specified as a numeric array. Y must be the same size and class as X.

Data Types: single | double | int8 | int16 | int32 | uint8 | uint16 | uint32 | logical

Output Arguments

Z — Difference image

numeric array

Difference image, returned as a numeric array. Z has the same class and size as X and Y. If X and Y are integer arrays, then imabsdiff truncates elements in the output that exceed the range of the integer type.

Tips

• If X is of class double, then use the expression abs(X-Y) instead of this function.

• If X is of class logical, then use the expression XOR(X,Y) instead of this function.

• When X and Y are of class uint8, int16, or single, then imabsdiff can use hardware optimization to run faster.

Extended Capabilities

C/C++ Code Generation

Generate C and C++ code using MATLAB® Coder™.

imabsdiff supports the generation of C code (requires MATLAB^® Coder™). For more information, see Code Generation for Image Processing.

GPU Code Generation
Generate CUDA® code for NVIDIA® GPUs using GPU 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 Image Processing on a GPU.

Version History

Introduced before R2006a

R2022b: Support for thread-based environments

imabsdiff now supports thread-based environments.