matlab的图像拼接程序(20210119152549)

mat lab的图像拼接程

序

-CAL-FENGHAI-(2020YEAR-YICAI) JINGBIAN

ll=imread{,,)；%6dTAEuODpAp¥dy2All%6D j u j A

ll=double(ll);

[hl wl dl]=size(ll);%TEOEdl±al2lldU±a>>0dl

I2= imread(n)；

I2=double(l2);

[h2 w2 d2]=size(l2);

%show input images and prompt for correspondences figure;subplot( 1,2,1)； image(ll/255); axis image; hold on; title(*first input image')；

[XI Yl]=ginput(2); %get two points from the usersubplot(l z2,2); image(l2/255); axis image; hold on;

title('sec ond input image*)；

[X2 Y2]=ginput(2); %get two points from the user %estimate parameter vector(t);

Z=[X2' Y2'； Y2'・X2'； HOOjOOll]1；

xp=[Xl; Yl];

t=Z\xp; %solve the I in ear system

a=t(l); %=s cos(alpha)

b=t(2);%=s sin(alpha)

tx=t(3);

ty=t(4);

% con struct transformation matrix(T)

T=[a b tx;・b a ty; 0 0 1];

% warp incoming corners to determine the size of the output image(in to out) cp二T*[l 1 w2 w2; 1 h2 1 h2; 1 111];

Xpr=min([cp(l/:)/O]): max([cp(l/:)/wl]);%min x:maxx

Ypr=min([cp(2/:)/0]): max([cp(2/:)/hl]); %min y: max y [Xp/Yp]=ndgrid(Xpr/ Ypr);

[wp hp]=size(Xp); %=size(Yp)

% do backwards transform (from out to in)

X=T\[Xp(:) Yp(:) ones(wp*hp/l)]'；%warp

%re-sample pixel values with bilinear interpolation

clear Ip;

xl二reshape(X(b：)Mp,hp)‘;

yl=reshape(X(2/:)/wp/hp)1;

lp(:/:/l)=interp2(l2(:/:/l)/xl/ yl, '♦bilinear*); %red

Ip(:/:/2)=interp2(l2(:/:/2)/xl/ yl, '♦bilinear1)；%green lp(:z:/3)=interp2(l2(:/:/3)/xl/ yl, ^bilinear1)；%blue

% offset and copy original image into the warped image offset= -rounddmindcpfl/)^]) min([cp(2,:),0])]); lp(l+offset ⑵:hl+offset(2), 1+off set {1): wl+offset (1 )z:); doublefllflihl.liwl,:));

%show the result

figure; image(lp/255); axis image;

title('mosaic image')；

ll=double(imread(n));

[hl wl dl]=size(ll);%TEOEdl±aPll6lJ±agl

I2=double(imread(n));

[h2 w2 d2]=size(l2);

%show input images and prompt for correspondences

figure; subplot(l,2z l); image(ll/255); axis image; hold on; title('first input image');

[XI Yl]=ginput(2); %get two points from the user

subplot(122); image(l2/255); axis image; hold on;

title('sec ond input image1)；

[X2 Y2]=ginput(2); %get two points from the user

%estimate parameter

vector(t);

Z=[X2' Y2'； Y2'-X2' ；1100;0011]'；

xp=[Xl; Yl];

t=Z\xp; %solve the linear system

%%

a=t(l); %=s cos(alpha)

b=t(2); %=s sin(alpha)

tx=t(3);

ty=t(4);

%construct transformation matrix(T)

T=[a b tx;・b a ty; 0 0 1];

%warp incoming corners to determine the size of the output image(in to out) cp=T*[l 1 w2 w2; 1 h2 1 h2;

1 111];

Xpr=min([cp(l/:)/O]):max([cp(l/:)/wl]);% min x: max x

Ypr=min([cp(2/:)/0]):max([cp(2/:)/hl]); %min y :max y (Xp/Yp]=ndgrid(Xpr/ Ypr);

[wp hp]=size(Xp); %=size(Yp) OaAiOD^di® 3d7£-»dN±»E¥po

% do backwards transform(from out to in)

X=T\(Xp(:) Yp(:) ones(wp*hp/ I)]1; %warp

%re-sample pixel values with bilinear interpolation

clear Ip;

xl二reshape(X(：U：), wp, hp)1;

yl=reshape(X(2z:), wp, hp)1; lp(:/:/l)=interp2(l2(:/:/l)/xl, yl,^bilinear1); %red Ip(:/:/2)=interp2(l2(:/:/2)/ xi, yl, '^bilinear'); %green lp(:/:/3)=interp2(l2(:/:,3)/ xl, yl, '^bilinear1)；%blue %offset and copy original image into the warped image offset= ・round([min([cp(l,:),0]) min([cp(2,:),0])]);

lp(l+offset⑵:hl+offset(2), l+offset(l):wl+offset(l)#:);

%%

double(ll(l:hl, l:wl/));

%show the result

figure; image(lp/255); axis image;

title('mosaic image')；