matlabjuanji.txt

在matlab 环境下运用卷积算法实现对图像损坏区域的修复。

%main   function 
%-------------------- 
img       =   imread( 'gh2.bmp '); 
image   =   rgb2gray(img); 
theta_input   =   240.0; 
additional_theta   =   theta_input   +   90; 
w   =   2*pi; 
t   =   0.5; 

[G2a,   G2b,   G2c] =   imgG2Init(image); 
[H2a,   H2b,   H2c,   H2d] =   imgH2Init(image); 

[G2_theta]   =   imgG2theta(G2a,   G2b,   G2c,   theta_input); 
[H2_theta]   =   imgH2theta(H2a,   H2b,   H2c,   H2d,   theta_input); 
[G2_additional_theta]   =   imgG2theta(G2a,   G2b,   G2c,   additional_theta); 
for   frame   =   1:60 
  result   =   cos(w*t)*G2_theta   +   sin(w*t)*H2_theta-G2_additional_theta; 
  imshow(result); 
  for   j=1:9999 
  a   =   j; 
  end; 
  t   =   t   +   0.09; 
end 
以上是主函数，下面贴出几个用到的函数： 
%   Interpolation   functions   (note   that   theta   is   in   radians): 
%         G2_ka   =   cos(theta)^2; 
%         G2_kb   =   -2*cos(theta)*sin(theta);   
%         G2_kc   =   sin(theta)^2;   
% 
%   G2   at   theta   is   defined   as   follows: 
%         G_2   =   G2_ka*G2a   +   G2_kb*G2b   +   G2_kc*G2c 
function   [G2a,   G2b,   G2c]   =   imgG2Init(img) 
  
  F1_G2   =   [   0.0094     0.1148     0.3964   -0.0601   -0.9213   -0.0601   0.3964   0.1148   0.0094]; 
  F2_G2   =   [   0.0008     0.0176     0.1660     0.6383     1.0           0.6383   0.1660   0.0176   0.0008]; 
  F3_G2   =   [-0.0028   -0.0480   -0.3020   -0.5806     0.0           0.5806   0.3020   0.0480   0.0028];   
  
  G2a   =   conv2(F1_G2,F2_G2,img, 'same '); 
  G2b   =   conv2(F3_G2,F3_G2,img, 'same '); 
  G2c   =   conv2(F2_G2,F1_G2,img, 'same '); 

%   -   Assumption:   theta   given   in   degrees 
function   [G2_theta]   =   imgG2theta(G2a,   G2b,   G2c,   theta_input) 
syms   theta 

%   ---   G2   interpolation   functions   --- 
G2_ka   =   cos((pi/180)*theta)^2; 
G2_kb   =   -2*cos((pi/180)*theta)*sin((pi/180)*theta);   
G2_kc   =   sin((pi/180)*theta)^2; 
%   ---           

G2_theta   =   subs(G2_ka,theta_input)*G2a... 
                      +   subs(G2_kb,theta_input)*G2b... 
                      +   subs(G2_kc,theta_input)*G2c;   


%   Interpolation   functions   (note   that   theta   is   in   radians): 
%         H2_ka   =   cos(theta)^3;   
%         H2_kb   =   -3*(cos(theta)^2)*sin(theta); 
%         H2_kc   =     3*cos(theta)*(sin(theta)^2); 
%         H2_kd   =   -sin(theta)^3; 
% 
%   H2   at   theta   is   defined   as   follows: 
%         H_2   =   H2_ka*H2a   +   H2_kb*H2b   +   H2_kc*H2c 
function   [H2a,   H2b,   H2c,   H2d]   =   imgH2Init(img) 

F1_H2   =   [-0.0098     -0.0618     0.0998     0.7551     0.0         -0.7551     -0.0998     0.0618     0.0098]; 
F2_H2   =   [   0.0008       0.0176     0.1660     0.6383     1.0           0.6383       0.1660     0.0176     0.0008]; 
F3_H2   =   [-0.0020     -0.0354   -0.2225   -0.4277     0.0           0.4277       0.2225     0.0354     0.0020]; 
F4_H2   =   [   0.0048       0.0566     0.1695   -0.1889   -0.7349   -0.1889       0.1695     0.0566     0.0048]; 


H2a   =   conv2(F2_H2,F1_H2,img, 'same '); 
H2b   =   conv2(F3_H2,F4_H2,img, 'same '); 
H2c   =   conv2(F4_H2,F3_H2,img, 'same '); 
H2d   =   conv2(F1_H2,F2_H2,img, 'same '); 

%   -   Assumption:   theta   given   in   degrees 

function   [H2_theta]   =   imgH2theta(H2a,   H2b,   H2c,   H2d,   theta_input) 
syms   theta 

%   ---   H2   interpolation   functions   --- 
H2_ka   =   cos((pi/180)*theta)^3;   
H2_kb   =   -3*(cos((pi/180)*theta)^2)*sin((pi/180)*theta); 
H2_kc   =     3*cos((pi/180)*theta)*(sin((pi/180)*theta)^2); 
H2_kd   =   -sin((pi/180)*theta)^3; 
%   --- 

H2_theta   =   subs(H2_ka,theta_input)*H2a... 
                      +   subs(H2_kb,theta_input)*H2b... 
                      +   subs(H2_kc,theta_input)*H2c... 
                      +   subs(H2_kd,theta_input)*H2d;