imgaussfilt3

3-D Gaussian filtering of 3-D images

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Syntax

B = imgaussfilt3(A)
B = imgaussfilt3(A,sigma)
B = imgaussfilt3(___,Name,Value)

Description

example

B = imgaussfilt3(A) filters 3-D image A with a 3-D Gaussian smoothing kernel with standard deviation of 0.5, and returns the filtered image in B.

B = imgaussfilt3(A,sigma) filters 3-D image A with a 3-D Gaussian smoothing kernel with standard deviation specified by sigma.

B = imgaussfilt3(___,Name,Value) uses name-value pair arguments to control aspects of the filtering.

Examples

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Open Live Script

Load MRI data and display it.

vol = load('mri');
figure
montage(vol.D)
title('Original image volume')

Smooth the image with a 3-D Gaussian filter. 

siz = vol.siz;
vol = squeeze(vol.D);   
sigma = 2;
 
volSmooth = imgaussfilt3(vol, sigma);
  
figure
montage(reshape(volSmooth,siz(1),siz(2),1,siz(3)))
title('Gaussian filtered image volume')

Input Arguments

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Image to be filtered, specified as a 3-D numeric array.

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

Standard deviation of the Gaussian distribution, specified as positive number or a 3-element vector of positive numbers. If sigma is a scalar, then imgaussfilt3 uses a cubic Gaussian kernel.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64

Name-Value Pair Arguments

Specify optional comma-separated pairs of Name,Value arguments. Name is the argument name and Value is the corresponding value. Name must appear inside quotes. You can specify several name and value pair arguments in any order as Name1,Value1,...,NameN,ValueN.

Example: volSmooth = imgaussfilt3(vol,sigma,'padding','circular');

Size of the Gaussian filter, specified as a scalar or 3-element vector of positive, odd, integers. If you specify a scalar, then imgaussfilt3 uses a cubic filter. The default filter size is 2*ceil(2*sigma)+1.

Example: volSmooth = imgaussfilt3(vol,sigma,'FilterSize',5);

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64

Image padding, specified as one of the following.

ValueDescription
numeric scalarPad image with elements of constant value.
'circular'

Pad with circular repetition of elements within the dimension.

'replicate'

Pad by repeating border elements of array.

'symmetric'

Pad image with mirror reflections of itself.

Example: volSmooth = imgaussfilt3(vol,sigma,'padding','circular');

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | logical | char | string

Domain in which to perform filtering, specified as one of the following values.

Filter Domain Description
'auto'Perform convolution in the spatial or frequency domain, based on internal heuristics.
'frequency'Perform convolution in the frequency domain.
'spatial'Perform convolution in the spatial domain.

Example: volSmooth = imgaussfilt3(vol,sigma,'FilterDomain','frequency');

Data Types: char | string

Output Arguments

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

Tips

  • If image A contains Infs or NaNs, then the behavior of imgaussfilt3 for frequency domain filtering is undefined. This can happen if you set the 'FilterDomain' parameter to 'frequency' or if you set it to 'auto' and imgaussfilt3 uses frequency domain filtering. To restrict the propagation of Infs and NaNs in the output in a manner similar to imfilter, consider setting the 'FilterDomain' parameter to 'spatial'.

  • If you set the 'FilterDomain' parameter to 'auto', then imgaussfilt3 uses an internal heuristic to determine whether spatial or frequency domain filtering is faster. This heuristic is machine-dependent and may vary for different configurations. For optimal performance, try both options, 'spatial' and 'frequency', to determine the best filtering domain for your image and kernel size.

  • If you do not specify the 'Padding' parameter, then imgaussfilt3 uses 'replicate' padding by default, which is different from the default used by imfilter.

Extended Capabilities

See Also

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Introduced in R2015a

Image Processing Toolbox Documentation

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