Matlab中fspecial的用法

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来源：https://blog.csdn.net/hustrains/article/details/9153553

Fspecial函数用于创建预定义的滤波算子，会与imfilter搭配使用，其语法格式为：

h = fspecial(type)h = fspecial(type,parameters,sigma)

参数type制定算子类型，parameters指定相应的参数，具体格式为：
type='average'，为均值滤波，参数为n，代表模版尺寸，用向量表示，默认值为[3,3]。
type= 'gaussian'，为高斯低通滤波器，参数有两个，n表示模版尺寸，默认值为[3,3]，sigma表示滤波器的标准差，单位为像素，默认值为

0.5。

When used with the 'average' filter type, the default filter size is [3 3]. When used with the Laplacian of Gaussian ('log') filter type, the default filter size is [5 5].
type= 'laplacian'，为拉普拉斯算子，参数为alpha，用于控制拉普拉斯算子的形状，取值范围为[0,1]，默认值为0.2。
type= 'log'，为拉普拉斯高斯算子，参数有两个，n表示模版尺寸，默认值为[3,3]，sigma为滤波器的标准差，单位为像素，默认值为0.5
type= 'prewitt'，为prewitt算子，用于边缘增强，无参数。
type= 'sobel'，为著名的sobel算子，用于边缘提取，无参数。
type= 'unsharp'，为对比度增强滤波器，参数alpha用于控制滤波器的形状，范围为[0,1]，默认值为0.2。

例子：

>> G=fspecial('gaussian',5)%参数为5，表示产生5*5的gaussian矩阵，如果没有，默认为3*3的矩阵。

G = 0.0000 0.0000 0.0002 0.0000 0.0000 0.0000 0.0113 0.0837 0.0113 0.0000 0.0002 0.0837 0.6187 0.0837 0.0002 0.0000 0.0113 0.0837 0.0113 0.0000 0.0000 0.0000 0.0002 0.0000 0.0000

>> G=fspecial('gaussian',5,1.5)%1.5为滤波器的标准差。

G = 0.0144 0.0281 0.0351 0.0281 0.0144 0.0281 0.0547 0.0683 0.0547 0.0281 0.0351 0.0683 0.0853 0.0683 0.0351 0.0281 0.0547 0.0683 0.0547 0.0281 0.0144 0.0281 0.0351 0.0281 0.0144

>> G=fspecial('average')%默认为3*3的矩阵。均值滤波

G = 0.1111 0.1111 0.1111 0.1111 0.1111 0.1111 0.1111 0.1111 0.1111

>> G=fspecial('average',5)%会产生5*5的矩阵。
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来源参考：https://ww2.mathworks.cn/help/images/ref/fspecial.html?searchHighlight=fspecial&s_tid=doc_srchtitle#d117e81606

fspecial

Create predefined 2-D filter

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Syntax

h = fspecial(type)

h = fspecial('average',hsize)

h = fspecial('disk',radius)

h = fspecial('gaussian',hsize,sigma)

h = fspecial('laplacian',alpha)

h = fspecial('log',hsize,sigma)

h = fspecial('motion',len,theta)

h = fspecial('prewitt')

h = fspecial('sobel')

Description

example

h = fspecial(type) creates a two-dimensional filter h of the specified type. Some of the filter types have optional additional parameters, shown in the following syntaxes. fspecial returns h as a correlation kernel, which is the appropriate form to use with imfilter.

h = fspecial('average',hsize) returns an averaging filter h of size hsize.

h = fspecial('disk',radius) returns a circular averaging filter (pillbox) within the square matrix of size 2*radius+1.

h = fspecial('gaussian',hsize,sigma) returns a rotationally symmetric Gaussian lowpass filter of size hsize with standard deviation sigma. Not recommended. Use imgaussfilt or imgaussfilt3 instead.

h = fspecial('laplacian',alpha) returns a 3-by-3 filter approximating the shape of the two-dimensional Laplacian operator, alpha controls the shape of the Laplacian.

h = fspecial('log',hsize,sigma) returns a rotationally symmetric Laplacian of Gaussian filter of size hsize with standard deviation sigma.

h = fspecial('motion',len,theta) returns a filter to approximate, once convolved with an image, the linear motion of a camera. len specifies the length of the motion and theta specifies the angle of motion in degrees in a counter-clockwise direction. The filter becomes a vector for horizontal and vertical motions. The default len is 9 and the default theta is 0, which corresponds to a horizontal motion of nine pixels.

h = fspecial('prewitt') returns a 3-by-3 filter that emphasizes horizontal edges by approximating a vertical gradient. To emphasize vertical edges, transpose the filter h'.

[ 1 1 1
0 0 0
-1 -1 -1 ]

h = fspecial('sobel') returns a 3-by-3 filter that emphasizes horizontal edges using the smoothing effect by approximating a vertical gradient. To emphasize vertical edges, transpose the filter h'.

[ 1 2 1
0 0 0
-1 -2 -1 ]

Examples

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Create Various Filters and Filter an Image

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Read image and display it.

I = imread('cameraman.tif');
imshow(I);

Create a motion filter and use it to blur the image. Display the blurred image.

H = fspecial('motion',20,45);
MotionBlur = imfilter(I,H,'replicate');
imshow(MotionBlur);

Create a disk filter and use it to blur the image. Display the blurred image.

H = fspecial('disk',10);
blurred = imfilter(I,H,'replicate');
imshow(blurred);

Input Arguments

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`type` — Type of filter
`'average'` | `'disk'` | `'gaussian'` | `'laplacian'` | `'log'` | `'motion'` | `'prewitt'` | `'sobel'`

Type of filter, specified as one of the following values:

Value	Description
`'average'`	Averaging filter
`'disk'`	Circular averaging filter (pillbox)
`'gaussian'`	Gaussian lowpass filter. Not recommended. Use `imgaussfilt` or `imgaussfilt3` instead.
`'laplacian'`	Approximates the two-dimensional Laplacian operator
`'log'`	Laplacian of Gaussian filter
`'motion'`	Approximates the linear motion of a camera
`'prewitt'`	Prewitt horizontal edge-emphasizing filter
`'sobel'`	Sobel horizontal edge-emphasizing filter

Data Types: char | string

`hsize` — Size of the filter
positive integer | 2-element vector of positive integers

Size of the filter, specified as a positive integer or 2-element vector of positive integers. Use a vector to specify the number of rows and columns in h. If you specify a scalar, then h is a square matrix.

When used with the 'average' filter type, the default filter size is [3 3]. When used with the Laplacian of Gaussian ('log') filter type, the default filter size is [5 5].

Data Types: double

`radius` — Radius of a disk-shaped filter
`5` (default) | positive number

Radius of a disk-shaped filter, specified as a positive number.

Data Types: double

`sigma` — Standard deviation
`0.5` (default) | positive number

Standard deviation, specified as a positive number.

Data Types: double

`alpha` — Shape of the Laplacian
`0.2` (default) | scalar in the range [0 1]

Shape of the Laplacian, specified as a scalar in the range [0 1].

Data Types: double

`len` — Linear motion of camera
`9` (default) | numeric scalar

Linear motion of camera, specified as a numeric scalar, measured in pixels.

Data Types: double

`theta` — Angle of camera motion
`0` (default) | numeric scalar

Angle of camera motion, specified as a numeric scalar, measured in degrees, in a counter-clockwise direction.

Data Types: double

Output Arguments

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`h` — Correlation kernel
matrix

Correlation kernel, returned as a matrix.

Data Types: double

Algorithms

Averaging filters:

ones(n(1),n(2))/(n(1)*n(2))

Gaussian filters:

hg(n1,n2)=e−(n21+n22)2σ2

h(n1,n2)=hg(n1,n2)n1n2hg

Laplacian filters:

∇2=∂2∂x2+∂2∂y2

∇2=4(α+1)α41−α4α41−α4−11−α4α41−α4α4

Laplacian of Gaussian (LoG) filters:

hg(n1,n2)=e−(n21+n22)2σ2

h(n1,n2)=(n21+n22−2σ2)hg(n1,n2)σ4n1n2hg

Note that fspecial shifts the equation to ensure that the sum of all elements of the kernel is zero (similar to the Laplace kernel) so that the convolution result of homogeneous regions is always zero.

Motion filters:

Construct an ideal line segment with the length and angle specified by the arguments len and theta, centered at the center coefficient of h.
For each coefficient location (i,j), compute the nearest distance between that location and the ideal line segment.
h = max(1 - nearest_distance, 0);
Normalize h: h = h/(sum(h(:)))

Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using MATLAB Coder.

Usage notes and limitations:

fspecial supports the generation of C code (requires MATLAB Coder). For more information, see Code Generation for Image Processing.
When generating code, all inputs must be constants at compilation time.

GPU Code Generation
Generate CUDA code for NVIDIA GPUs using GPU Coder.

Usage notes and limitations:

When generating code, all inputs must be constants at compilation time.

Topics

Filter Images Using Predefined Filters
What Is Image Filtering in the Spatial Domain?

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