fspecial

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function h = fspecial(varargin)

%FSPECIAL Create 2-D special filters.

% H = FSPECIAL(TYPE) creates a two-dimensional filter H of the

% specified type. Possible values for TYPE are:

%

% 'average' averaging filter

% 'disk' circular averaging filter% 'gaussian' Gaussian lowpass filter

% 'laplacian' filter approximating the 2-D Laplacian operator

% 'log' Laplacian of Gaussian filter

% 'motion' motion filter

% 'prewitt' Prewitt horizontal edge-emphasizing filter

% 'sobel' Sobel horizontal edge-emphasizing filter

% 'unsharp' unsharp contrast enhancement filter

%

% Depending on TYPE, FSPECIAL may take additional parameters

% which you can supply. These parameters all have default

% values.

%% H = FSPECIAL('average',HSIZE) returns an averaging filter H of size

% HSIZE. HSIZE can be a vector specifying the number of rows and columns in

% H or a scalar, in which case H is a square matrix.

% The default HSIZE is [3 3].

%

% H = FSPECIAL('disk',RADIUS) returns a circular averaging filter

% (pillbox) within the square matrix of side 2*RADIUS+1.

% The default RADIUS is 5.

%

% H = FSPECIAL('gaussian',HSIZE,SIGMA) returns a rotationally

% symmetric Gaussian lowpass filter of size HSIZE with standard

% deviation SIGMA (positive). HSIZE can be a vector specifying the% number of rows and columns in H or a scalar, in which case H is a

% square matrix.

% The default HSIZE is [3 3], the default SIGMA is 0.5.

%

% H = FSPECIAL('laplacian',ALPHA) returns a 3-by-3 filter

% approximating the shape of the two-dimensional Laplacian

% operator. The parameter ALPHA controls the shape of the

% Laplacian and must be in the range 0.0 to 1.0.

% The default ALPHA is 0.2.

%

% H = FSPECIAL('log',HSIZE,SIGMA) returns a rotationally symmetric

% Laplacian of Gaussian filter of size HSIZE with standard deviation% SIGMA (positive). HSIZE can be a vector specifying the number of rows

% and columns in H or a scalar, in which case H is a square matrix.

% The default HSIZE is [5 5], the default SIGMA is 0.5.

%

% H = FSPECIAL('motion',LEN,THETA) returns a filter to approximate, once

% convolved with an image, the linear motion of a camera by LEN pixels,

% with an angle of THETA degrees in a counter-clockwise direction. The

% filter becomes a vector for horizontal and vertical motions. The

% default LEN is 9, the default THETA is 0, which corresponds to a

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rad = p2;

crad = ceil(rad-0.5);

[x,y] = meshgrid(-crad:crad,-crad:crad);

maxxy = max(abs(x),abs(y));

minxy = min(abs(x),abs(y));

m1 = (rad^2 < (maxxy+0.5).^2 + (minxy-0.5).^2).*(minxy-0.5) + ...

(rad^2 >= (maxxy+0.5).^2 + (minxy-0.5).^2).* ...sqrt(rad^2 - (maxxy + 0.5).^2);

m2 = (rad^2 > (maxxy-0.5).^2 + (minxy+0.5).^2).*(minxy+0.5) + ...

(rad^2 (maxxy-0.5).^2 + (minxy-0.5).^2)) | ...

((minxy==0)&(maxxy-0.5 < rad)&(maxxy+0.5>=rad))));

sgrid = sgrid + ((maxxy+0.5).^2 + (minxy+0.5).^2 < rad^2);

sgrid(crad+1,crad+1) = min(pi*rad^2,pi/2);if ((crad>0) & (rad > crad-0.5) & (rad^2 < (crad-0.5)^2+0.25))

m1 = sqrt(rad^2 - (crad - 0.5).^2);

m1n = m1/rad;

sg0 = 2*(rad^2*(0.5*asin(m1n) + 0.25*sin(2*asin(m1n)))-m1*(crad-0.5));

sgrid(2*crad+1,crad+1) = sg0;

sgrid(crad+1,2*crad+1) = sg0;

sgrid(crad+1,1) = sg0;

sgrid(1,crad+1) = sg0;

sgrid(2*crad,crad+1) = sgrid(2*crad,crad+1) - sg0;

sgrid(crad+1,2*crad) = sgrid(crad+1,2*crad) - sg0;

sgrid(crad+1,2) = sgrid(crad+1,2) - sg0;

sgrid(2,crad+1) = sgrid(2,crad+1) - sg0;end

sgrid(crad+1,crad+1) = min(sgrid(crad+1,crad+1),1);

h = sgrid/sum(sgrid(:));

case 'gaussian' % Gaussian filter

siz = (p2-1)/2;

std = p3;

[x,y] = meshgrid(-siz(2):siz(2),-siz(1):siz(1));

arg = -(x.*x + y.*y)/(2*std*std);

h = exp(arg);

h(h

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alpha = p2;

alpha = max(0,min(alpha,1));

h1 = alpha/(alpha+1); h2 = (1-alpha)/(alpha+1);

h = [h1 h2 h1;h2 -4/(alpha+1) h2;h1 h2 h1];

case 'log' % Laplacian of Gaussian

% first calculate Gaussiansiz = (p2-1)/2;

std2 = p3^2;

[x,y] = meshgrid(-siz(2):siz(2),-siz(1):siz(1));

arg = -(x.*x + y.*y)/(2*std2);

h = exp(arg);

h(h

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% unfold half-matrix to the full size

h = rot90(dist2line,2);

h(end+[1:end]-1,end+[1:end]-1) = dist2line;

h = h./(sum(h(:)) + eps*len*len);

if cosphi>0,h = flipud(h);

end

case 'prewitt' % Prewitt filter

h = [1 1 1;0 0 0;-1 -1 -1];

case 'sobel' % Sobel filter

h = [1 2 1;0 0 0;-1 -2 -1];

case 'unsharp' % Unsharp filter

alpha = p2;

h = [0 0 0;0 1 0;0 0 0] - fspecial( 'laplacian',alpha);

end

%%%

%%% ParseInputs

%%%

function [type, p2, p3] = ParseInputs(varargin)

% default values

type = '';

p2 = [];p3 = [];

% Check the number of input arguments.

checknargin(1,3,nargin,mfilename);

% Determine filter type from the user supplied string.

type = varargin{1};

type = checkstrs(type,{ 'gaussian','sobel' ,'prewitt','laplacian','log',...

'average','unsharp','disk' ,'motion'},mfilename,'TYPE',1);

% default values

switch typecase 'average'

p2 = [3 3]; % siz

case 'disk'

p2 = 5; % rad

case 'gaussian'

p2 = [3 3]; % siz

p3 = 0.5; % std

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case {'laplacian', 'unsharp'}

p2 = 1/5; % alpha

case 'log'

p2 = [5 5]; % siz

p3 = 0.5; % std

case 'motion'

p2 = 9; % len

p3 = 0; % theta

end

switch nargin

case 1

% FSPECIAL('average')

% FSPECIAL('disk')

% FSPECIAL('gaussian')% FSPECIAL('laplacian')

% FSPECIAL('log')

% FSPECIAL('motion')

% FSPECIAL('prewitt')

% FSPECIAL('sobel')

% FSPECIAL('unsharp')

% Nothing to do here; the default values have

% already been assigned.

case 2

% FSPECIAL('average',N)

% FSPECIAL('disk',RADIUS)% FSPECIAL('gaussian',N)

% FSPECIAL('laplacian',ALPHA)

% FSPECIAL('log',N)

% FSPECIAL('motion',LEN)

% FSPECIAL('unsharp',ALPHA)

p2 = varargin{2};

switch type

case {'sobel','prewitt'}

msg = sprintf( '%s: Too many arguments for this type of filter.' , upper

(mfilename));

eid = sprintf( 'Images:%s:tooManyArgsForThisFilter' , mfilename);error(eid,msg);

case {'laplacian','unsharp'}

checkinput(p2,{ 'double'},{'nonnegative','real',...

'nonempty','finite','scalar'},...

mfilename, 'ALPHA',2);

if p2 > 1

msg = sprintf( '%s: ALPHA should be less than or equal 1 and greater than

0.', upper(mfilename));

eid = sprintf( 'Images:%s:outOfRangeAlpha', mfilename);

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error(eid,msg);

end

case {'disk','motion'}

checkinput(p2,{ 'double'},{'positive','finite','real' ,'nonempty','scalar'},

mfilename,'RADIUS or LEN',2);

case {'gaussian','log','average'}

checkinput(p2,{ 'double'},{'positive','finite','real' ,'nonempty','integer'},mfilename,'HSIZE',2);

if prod(size(p2)) > 2

msg = 'HSIZE should have 1 or 2 elements.' ;

eid = sprintf( 'Images:%s:wrongSizeN', mfilename);

error(eid,msg);

elseif (prod(size(p2))==1)

p2 = [p2 p2];

end

end

case 3% FSPECIAL('gaussian',N,SIGMA)

% FSPECIAL('log',N,SIGMA)

% FSPECIAL('motion',LEN,THETA)

p2 = varargin{2};

p3 = varargin{3};

switch type

case 'motion'


mfilename,'LEN',2);

checkinput(p3,{ 'double'},{'real','nonempty','finite','scalar'},

mfilename,'THETA',3);case {'gaussian','log'}

checkinput(p2,{ 'double'},{'positive','finite','real' ,'nonempty','integer'},

mfilename,'N',2);


mfilename,'SIGMA',3);

if prod(size(p2)) > 2

msg = sprintf( '%s: size(N) should be less than or equal 2.' , upper

(mfilename));

eid = sprintf( 'Images:%s:wrongSizeN', mfilename);

error(eid,msg);

elseif (prod(size(p2))==1)

p2 = [p2 p2];end

otherwise

msg = sprintf( '%s: Too many arguments for this type of filter.' , upper

(mfilename));

eid = sprintf( 'Images:%s:tooManyArgsForThisFilter' , mfilename);

error(eid,msg);

end

end

fspecial

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