matlab实现gabor filter (6)

代码：

%%%%%%%VERSION 3%%ANOTHER DESCRIBTION OF GABOR FILTER%The Gabor filter is basically a Gaussian (with variances sx and sy along x and y-axes respectively)%modulated by a complex sinusoid (with centre frequencies U and V along x and y-axes respectively) %described by the following equation%%%               1                -1     x  ^    y  ^%%% Gi(x,y) = ---------- * exp ([----{(----) 2+(----) 2}])*Mi(x,y,f); %            2*pi*sx*sy           2    sx       sy%%% i =1,2%%% M1(x,y,f) = cos[2*pi*f*sqrt(x^2+y^2)];%%% M2(x,y,f) = cos[2*pi*f*(x*cos(theta) + y*sin(theta)];%% Describtion :%% I : Input image%% Sx & Sy : Variances along x and y-axes respectively%% f : The frequency of the sinusoidal function%% theta : The orientation of Gabor filter%% G1 & G2 : The output filters as described above%% gabout1 & gabout2 : The output filtered images%%  Author : Ahmad poursaberi  e-mail : [e-mail]%%          Faulty of Engineering, Electrical&Computer Department,Tehran%%          University,Iran,June 2004function [G1,G2,gabout1,gabout2] = gaborfilter2(I,Sx,Sy,f,theta)if isa(I,'double')~=1     I = double(I);endfor x = -fix(Sx):fix(Sx)    for y = -fix(Sy):fix(Sy)        M1 = cos(2*pi*f*sqrt(x^2+y^2));        M2 = cos(2*pi*f*(x*cos(theta)+y*sin(theta)));        G1(fix(Sx)+x+1,fix(Sy)+y+1) = (1/(2*pi*Sx*Sy)) * exp(-.5*((x/Sx)^2+(y/Sy)^2))*M1;        G2(fix(Sx)+x+1,fix(Sy)+y+1) = (1/(2*pi*Sx*Sy)) * exp(-.5*((x/Sx)^2+(y/Sy)^2))*M2;    endendImgabout1 = conv2(I,double(imag(G1)),'same');Regabout1 = conv2(I,double(real(G1)),'same');Imgabout2 = conv2(I,double(imag(G2)),'same');Regabout2 = conv2(I,double(real(G2)),'same');gabout1 = sqrt(Imgabout1.*Imgabout1 + Regabout1.*Regabout1);gabout2 = sqrt(Imgabout2.*Imgabout2 + Regabout2.*Regabout2);

调用代码：

close all;clear all;clc;% 读入图像image=imread('C:\Users\watkins\Pictures\cartoon.jpg');grayImage=rgb2gray(image);grayImage=im2double(grayImage);% 显示读入图像imshow(grayImage);sx=32;sy=32;theta=[0 pi/4 2*pi/4 3*pi/4 4*pi/4 5*pi/4 6*pi/4 7*pi/4];gamma=1;psi=0;sigma=6; % 也可以为12lambda=[5 6 7 8 9];V=[4 5 6 7 8];U=[0 pi/4 2*pi/4 3*pi/4 4*pi/4 5*pi/4 6*pi/4 7*pi];%U=[1 2 3 4 5 6 7 8];% Creating 40 Gabor FiltersG = cell(5,8);for i = 1:5    for j = 1:8        G{i,j}=zeros(65,65);    endendfor i = 1:5    for j = 1:8        f=1/lambda(i);        %[T,gabout] = gaborfilter(grayImage,sx,sy,U(j),V(i));        %G{i,j} = T;        %G{i,j} = gaborfilter1(grayImage,sx,sy,f,theta(j));        [T1,T2] = gaborfilter2(grayImage,sx,sy,f,theta(j));        G{i,j} = T2;    endend% Showing Gabor Filtersfigure;for s = 1:5    for j = 1:8                subplot(5,8,(s-1)*8+j);                %imshow(real(G{s,j})/2-0.5,[]);        imshow(real(G{s,j}),[]);    endend

 

生成的滤波器组，第一个返回的滤波器组图像：

 

第二个生成的滤波器组图像：