imfilter

N-D filtering of multidimensional images

Syntax

B = imfilter(A,h)

B = imfilter(A,h,options,...)

Description

B = imfilter(A,h) filters the multidimensional array A with the multidimensional filter h and returns the result in B.

B = imfilter(A,h,options,...) performs multidimensional filtering according to one or more specified options.

Examples

Create Filter and Apply It

Read a color image into the workspace and display it.

originalRGB = imread('peppers.png');
imshow(originalRGB)

Create a motion-blur filter using the fspecial function.

h = fspecial('motion', 50, 45);

Apply the filter to the original image to create an image with motion blur. Note that imfilter is more memory efficient than some other filtering functions in that it outputs an array of the same data type as the input image array. In this example, the output is an array of uint8.

filteredRGB = imfilter(originalRGB, h);
figure, imshow(filteredRGB)

Filter the image again, this time specifying the replicate boundary option.

boundaryReplicateRGB = imfilter(originalRGB, h, 'replicate');
figure, imshow(boundaryReplicateRGB)

Filter Images Using imfilter with Convolution

By default, imfilter uses correlation because the toolbox filter design functions produce correlation kernels. Use the optional parameter to use convolution.

Create a sample matrix.

A = magic(5)

A = 5×5

    17    24     1     8    15
    23     5     7    14    16
     4     6    13    20    22
    10    12    19    21     3
    11    18    25     2     9

Create a filter.

h = [-1 0 1];

Filter using correlation, the default.

imfilter(A,h)

ans = 5×5

    24   -16   -16    14    -8
     5   -16     9     9   -14
     6     9    14     9   -20
    12     9     9   -16   -21
    18    14   -16   -16    -2

Filter using convolution, specifying imfilter with the optional parameter.

imfilter(A,h,'conv')

ans = 5×5

   -24    16    16   -14     8
    -5    16    -9    -9    14
    -6    -9   -14    -9    20
   -12    -9    -9    16    21
   -18   -14    16    16     2

Convert Image Class to Avoid Negative Output Values

In this example, the output of imfilter has negative values when the input is of class double. To avoid negative values, convert the image to a different data type before calling imfilter. For example, when the input type is uint8, imfilter truncates output values to 0. It might also be appropriate to convert the image to a signed integer type.

A = magic(5)

A = 5×5

    17    24     1     8    15
    23     5     7    14    16
     4     6    13    20    22
    10    12    19    21     3
    11    18    25     2     9

Filter the image with imfilter.

h = [-1 0 1];
imfilter(A,h)

ans = 5×5

    24   -16   -16    14    -8
     5   -16     9     9   -14
     6     9    14     9   -20
    12     9     9   -16   -21
    18    14   -16   -16    -2

Notice that the result has negative values. To avoid negative values in the output image, convert the input image to uint8 before performing the filtering. Since the input to imfilter is of class uint8, the output also is of class uint8, and imfilter truncates negative values to 0.

A = uint8(magic(5));
imfilter(A,h)

ans = 5x5 uint8 matrix

   24    0    0   14    0
    5    0    9    9    0
    6    9   14    9    0
   12    9    9    0    0
   18   14    0    0    0

Input Arguments

A — Image to be filtered

numeric array

Image to be filtered, specified as a numeric array of dimension.

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

h — Multidimensional filter

N-D array of data type double

Multidimensional filter, specified as an N-D array of data type double.

Data Types: double

options — Options that control the filtering operation

character vector | string scalar | numeric scalar

Options that control the filtering operation, specified as a character vector, string scalar, or numeric scalar. The following table lists all supported options.

Boundary Options

Option	Description
Padding Options
numeric scalar, X	Input array values outside the bounds of the array are assigned the value X. When no padding option is specified, the default is 0.
'symmetric'	Input array values outside the bounds of the array are computed by mirror-reflecting the array across the array border.
'replicate'	Input array values outside the bounds of the array are assumed to equal the nearest array border value.
'circular'	Input array values outside the bounds of the array are computed by implicitly assuming the input array is periodic.
Output Size
'same'	The output array is the same size as the input array. This is the default behavior when no output size options are specified.
'full'	The output array is the full filtered result, and so is larger than the input array.
Correlation and Convolution Options
'corr'	imfilter performs multidimensional filtering using correlation, which is the same way that filter2 performs filtering. When no correlation or convolution option is specified, imfilter uses correlation.
'conv'	imfilter performs multidimensional filtering using convolution.

Output Arguments

B — Filtered image

numeric array

Filtered image, returned as a numeric array of the same size and class as the input image, A.

Tips

• This function may take advantage of hardware optimization for data types uint8, uint16, int16, single, and double to run faster.

Algorithms

• The imfilter function computes the value of each output pixel using double-precision, floating-point arithmetic. If the result exceeds the range of the data type, then imfilter truncates the result to the allowed range of the data type. If it is an integer data type, then imfilter rounds fractional values.

• If you specify an even-sized kernel h, then the center of the kernel is floor((size(h) + 1)/2).

  For example, the center of 4-element filter [0.25 0.75 -0.75 -0.25] is the second element, 0.75. This filter gives identical results as filtering with the 5-element filter [0 0.25 0.75 -0.75 -0.25].

Extended Capabilities

C/C++ Code Generation

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

Usage notes and limitations:

• imfilter supports the generation of C code (requires MATLAB^® Coder™). Note that if you choose the generic MATLAB Host Computer target platform, imfilter generates code that uses a precompiled, platform-specific shared library. Use of a shared library preserves performance optimizations but limits the target platforms for which code can be generated. For more information, see Types of Code Generation Support in Image Processing Toolbox.

• When generating code, the input image, A, must be 2-D or 3-D. The value of the input argument, options, must be a compile-time constant.

• If you specify a large kernel h, a kernel that contains large values, or specify an image containing large values, you can see different results between MATLAB and generated code for floating point data types. This happens because of accumulation errors due to different algorithm implementations.

GPU Code Generation

Generate CUDA® code for NVIDIA® GPUs using GPU Coder™.

Usage notes and limitations:

• When generating code, the input image, A, must be 2-D or 3-D. The value of the input argument, options, must be a compile-time constant.

• If you specify a large kernel h, a kernel that contains large values, or specify an image containing large values, you can see different results between MATLAB and generated code for floating point data types. This happens because of accumulation errors due to different algorithm implementations.

• With CUDA^® toolkit v9.0, a bug in the NVIDIA^® optimization causes numerical mismatch between the results from the generated code and MATLAB. As a workaround, turn off the optimization by passing the following flags to the configuration object (cfg) before generating the code.

  cfg.GpuConfig.CompilerFlags = ‘-Xptxas -O0’

  NVIDIA is expected to fix this bug in CUDA toolkit v9.1.

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:

• The filtering kernel h must be a vector or 2-D matrix of data type double.

• If the image is filtered using a GPU, then imfilter computes the value of each output pixel using either single- or double-precision floating point, depending on the data type of A. If A contains double-precision or uint32 values, then imfilter uses double-precision values. For all other data types, imfilter uses single-precision. If A is an integer or logical array, then imfilter truncates output elements that exceed the range of the given type, and rounds fractional values.

For more information, see Image Processing on a GPU.

Version History

Introduced before R2006a

R2022b: Support for thread-based environments

imfilter now supports thread-based environments.