做相關的實驗，發現竟然沒找到的能直接用的matlab代碼，于是 google一下。

原理我覺得這個就講的挺好的：https://blog.csdn.net/hjimce/article/details/45716603

原文paper：?https://www.cs.virginia.edu/~connelly/class/2014/comp_photo/proj2/poisson.pdf

matlab代碼出處：https://www.mathworks.com/matlabcentral/fileexchange/62287-poisson-image-editing

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Demo.m??>?PIE_Gui?>?PIE

%Demo % T3 Demo code % source='source6.jpg'; target='target6.jpg'; result='result6.jpg'; I1 = imread(source); % SOURCE IMAGE I2 = imread(target); % DESTINATION IMAGE PIE_Gui(I1,I2,result,1,0);

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%%PIE_Gui % Author: Michael S. Brown, York University % % Simple Matlab GUI for selection a Region of Interest from Image1, and % pasting this into Image2. % % It calls a function called: PossionImageIntegration() % Currently this function is just a dummy function adds the ROI and % Dest together. This should generate the PIE image. % % Main functions: PIE_Gui % - Call back functions: myButtonPressDown, myButtonPressUp, % myMouseMotion, myKeypress % function PIE_Gui(I1, I2,FileName,Method,Color) % % ------------------- SELECT SOURCE ROI ------------------ % disp('USAGE: select a polygon region by using left mouse clicks to draw the vertices'); disp(' right nouse click to finish - you can then drag the selected region around.'); disp(' When you have it where you want it, double click left to cut it and paste to the next image.'); h = figure('MenuBar', 'none', 'Toolbar', 'none'); % open window [BW, xi, yi] = roipoly(I1); % this returns a binary image with white (1) in the mask % extract mask (crop image) [r,c] = find(BW == 1); % find the max values maxH = max(r) - min(r); % extract the height maxW = max(c) - min(c); % extract the width SRC = imcrop(I1,[min(c) min(r) maxW maxH]); % crop the image in the RIO % crop mask - make the mask RGB (3 layers) Mc = zeros(size(SRC)); % make a copy of Ic Mc(:,:,1) = imcrop(BW,[min(c) min(r) maxW maxH]); Mc(:,:,2) = imcrop(BW,[min(c) min(r) maxW maxH]); Mc(:,:,3) = imcrop(BW,[min(c) min(r) maxW maxH]); % % NOW SELECT PLACE TO PASTE % imshow(I2); title('Click and drag region to desired location. Press any key to integrate, press q to quit'); lh = line(xi, yi, 'Marker','.','LineStyle','-', 'Color', 'r', 'LineWidth',2); % Set up units and callback functions set(h, 'Units', 'pixels'); set(h,'WindowButtonDownFcn',@myButtonPressDown); set(h,'WindowButtonUpFcn',@myButtonPressUp); set(h, 'WindowButtonMotionFcn', @myMouseMotion); set(h, 'KeyPressFcn', @myKeyPress); myData.xi = xi-min(xi); myData.yi = yi-min(yi); myData.SRC = SRC; myData.DEST = I2; myData.Mc=Mc; myData.pressDown = 0; myData.line = lh; myData.curX = -1; myData.curY = -1; myData.Method=Method; myData.Color=Color; myData.FileName=FileName; set(h, 'UserData', myData); return %% % When button is pressed, call this function % function myButtonPressDown(obj,event_obj) myData = get(obj, 'UserData'); % get the user data (variable name does not have to be "myData" myData.pressDown = 1; % set mouse press = true p = get(gca,'CurrentPoint'); % get current position of mouse on the image curX = p(1,1); % extract the X position (it's a floating point value) curY = p(1,2); % extract the Y positions myData.curX = curX; myData.curY = curY; set(myData.line,'XData', myData.xi+curX, 'YData', myData.yi+curY); % Save the myData variable back to the object set(obj, 'UserData', myData); return %% % When button is released, call this function % function myButtonPressUp(obj,event_obj) myData = get(obj, 'UserData'); % get the user data myData.pressDown = 0; % set mouse press to be false set(obj, 'UserData', myData); % set the uer data (i.e. record mouse is not longer being pressed) return %% % Called anytime the mouse is moved % function myMouseMotion(obj,event_obj) myData = get(obj, 'UserData'); % get the user data if (myData.pressDown == 1) % we are only interested if the mouse is downp = get(gca,'CurrentPoint'); % get the current point from the imagecurX = p(1,1); % extract the point from the strange matlab datastructure return by previous line of codecurY = p(1,2);set(myData.line,'XData', myData.xi+curX, 'YData', myData.yi+curY);myData.curX = curX;myData.curY = curY;set(obj, 'UserData', myData); end return %% % Call when key any pressed any key % function myKeyPress(obj, event_obj) if (event_obj.Key == 'q')close(obj);return; end % Update the userdata in the object myData = get(obj, 'UserData'); if (myData.pressDown == 0) % if mouse is not pressedif (myData.curX == -1)disp('Select a location');return;end%% Get the source and destination image% Compute a new image (SImage) where the source is translated to% the correct position based on the last mouse position.%%DEST = myData.DEST;SRC = myData.SRC;tx = round(myData.curX);ty = round(myData.curY);[hh ww depth] = size(SRC);%use only the ROITRG(:,:,1)=DEST( ty:(ty+hh-1), tx:(tx+ww-1), 1 );TRG(:,:,2)=DEST( ty:(ty+hh-1), tx:(tx+ww-1), 2 );TRG(:,:,3)=DEST( ty:(ty+hh-1), tx:(tx+ww-1), 3 );% SImage( ty:(ty+hh-1), tx:(tx+ww-1), 1 ) = SRC(:,:,1);% SImage( ty:(ty+hh-1), tx:(tx+ww-1), 2 ) = SRC(:,:,2);% SImage( ty:(ty+hh-1), tx:(tx+ww-1), 3 ) = SRC(:,:,3);Mc = rgb2gray(myData.Mc);Mc(1,:)=0;Mc(end,:)=0;Mc(:,1)=0;Mc(:,end)=0;se = strel('disk',5);Mc = imerode( Mc,se);% Call the PIE function. It will returned the integrated imagenewI = PIE( TRG,SRC,Mc,myData.Method,myData.Color);%reconstructif size(newI,3)==1DEST=rgb2gray(DEST);DEST( ty:(ty+hh-1), tx:(tx+ww-1)) = newI(:,:);elseDEST( ty:(ty+hh-1), tx:(tx+ww-1), 1 ) = newI(:,:,1);DEST( ty:(ty+hh-1), tx:(tx+ww-1), 2 ) = newI(:,:,2);DEST( ty:(ty+hh-1), tx:(tx+ww-1), 3 ) = newI(:,:,3);end%PossionImageIntegration(SImage, DEST, tx, ty, ww, hh);imshow(DEST);imwrite(DEST,myData.FileName); end return

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%PIE function im_out = PIE( im_target,im_source,im_mask,m,c ) %PIE function: blends the source image with the target one based on the %boundary given as a BW mask using Poisson Image Editing (PIE) % -Usage- % im_out = PIE(targetImage,sourceImage,mask,0,0); %for seamless cloning % (true color) % im_out = PIE(targetImage,sourceImage,mask,1,0); %for mixing gradients % (true color) % im_out = PIE(targetImage,sourceImage,mask,0,1); %for seamless cloning % (grayscale) % im_out = PIE(targetImage,sourceImage,mask,1,1); %for mixing gradients % (grayscale) % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Citation: % Pérez, Patrick, Michel Gangnet, and Andrew Blake. % "Poisson image editing." ACM Transactions on Graphics (TOG). Vol. 22. % No. 3. ACM, 2003. % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % -Inputs- % im_target: target image % im_source: source image % im_mask: mask image % m: 0 for seamless cloning (default), and 1 for mixing gradients. % c: 0 for true color source and target images (default), and 1 for % grayscale source and target images. % -Outputs- % im_out: output image after blending the source image with the source % image based on the given mask (uint8). %% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %Initialization if nargin<3error('Please, use PIE(targetImage,sourceImage,mask)'); elseif nargin<4m=0; %use the default method (seamless cloning)c=0; %use the default image type (true color) elseif nargin<5c=0; %use the default image type (true color) end if size(im_target,1)~= size(im_source,1) || ...size(im_target,1)~= size(im_mask,1) || ...size(im_target,2)~= size(im_source,2) || ...size(im_target,2)~= size(im_mask,2) || ...size(im_target,3)~=size(im_source,3)error('Please, use images with the same size'); end %if the mask is not grayscale, convert it if size(im_mask,3)>1im_mask=rgb2gray(im_mask); end %convert source and target images to double for more precise computations im_target=double(im_target); im_source=double(im_source); %if we are working with true color, let m=3 otherwise, m=1 if c==0 %true color imagesc=3; %for the next for loop elsec=1;if size(im_source,3)>1im_source=rgb2gray(im_source);endif size(im_target,3)>1im_target=rgb2gray(im_target);endend %initially, output image = target image im_out=im_target; %create the laplacian mask for the second derivative of the source image laplacian_mask=[0 1 0; 1 -4 1; 0 1 0]; %normalize the mask image to assure that unknown pixels = 1 im_mask=mat2gray(im_mask); %convert it to logical to ignore any fractions (soft masks) im_mask=im_mask==1; %find the number of unknown pixels based on the mask n=size(find(im_mask==1),1); %create look up table map=zeros(size(im_mask)); %loop through the mask image to initialize the look up table for mapping counter=0; for x=1:size(map,1)for y=1:size(map,2)if im_mask(x,y)==1 %is it unknow pixel?counter=counter+1;map(x,y)=counter; %map from (x,y) to the corresponding pixel%in the 1D vectorendend end for i=1:c %for each color channel% loop through the mask image again to:%1- initialize the coefficient matrix%2- initialize the B vector%if the method is seamless cloning; so, intially put B= (-) laplacian of%im_source,%otherwise (mixing gradients), B= (-) max(laplacian of im_source, laplacian%of im_target)%create the coefficient matrix A%At most, there are 5 coefficients per row according to eq (3)%in the reportcoeff_num=5;%create the sparse matrix to save memoryA=spalloc(n,n,n*coeff_num);%create the right hand side of the linear system of equations (AX=B)B=zeros(n,1);if m==1 % mixing gradients%create the gradient mask for the first derivativegrad_mask_x=[-1 1];grad_mask_y=[-1;1]; %get the first derivative of the target imageg_x_target=conv2(im_target(:,:,i),grad_mask_x, 'same');g_y_target=conv2(im_target(:,:,i),grad_mask_y, 'same');g_mag_target=sqrt(g_x_target.^2+g_y_target.^2);%get the first derivative of the source imageg_x_source=conv2(im_source(:,:,i),grad_mask_x, 'same');g_y_source=conv2(im_source(:,:,i),grad_mask_y, 'same');g_mag_source=sqrt(g_x_source.^2+g_y_source.^2);%work with 1-Dg_mag_target=g_mag_target(:);g_mag_source=g_mag_source(:);%initialize the final gradient with the source gradientg_x_final=g_x_source(:);g_y_final=g_y_source(:);%if the gradient of the target image is larger than the gradient of%the source image, use the target's gradient insteadg_x_final(abs(g_mag_target)>abs(g_mag_source))=...g_x_target(g_mag_target>g_mag_source);g_y_final(abs(g_mag_target)>abs(g_mag_source))=...g_y_target(g_mag_target>g_mag_source);%map to 2-Dg_x_final=reshape(g_x_final,size(im_source,1),size(im_source,2));g_y_final=reshape(g_y_final,size(im_source,1),size(im_source,2));%get the final laplacian of the combination between the source and%target images lap=second deriv of x + second deriv of ylap=conv2(g_x_final,grad_mask_x, 'same');lap=lap+conv2(g_y_final,grad_mask_y, 'same');else%create the laplacian of the source imagelap=conv2(im_source(:,:,i),laplacian_mask, 'same');endcounter=0;for x=1:size(map,1)for y=1:size(map,2)if im_mask(x,y)==1counter=counter+1;A(counter,counter)=4; %the diagonal represent the current pixel%check the boundaryif im_mask(x-1,y)==0 %known left pixelB(counter)=im_target(x-1,y,i); %add it to Belse %unknown boundaryA(counter,map(x-1,y))=-1; %set its coefficient to -1endif im_mask(x+1,y)==0 %known right pixelB(counter)=B(counter)+im_target(x+1,y,i); %add it to Belse %unknown boundaryA(counter,map(x+1,y))=-1; %set its coefficient to -1endif im_mask(x,y-1)==0 %known bottom pixelB(counter)=B(counter)+im_target(x,y-1,i); %add it to Belse %unknown boundaryA(counter,map(x,y-1))=-1; %set its coefficient to -1endif im_mask(x,y+1)==0 %known top pixelB(counter)=B(counter)+im_target(x,y+1,i); %add it to Belse %unknown boundaryA(counter,map(x,y+1))=-1; %set its coefficient to -1end%update the B vector with the laplacian valueB(counter)=B(counter)-lap(x,y);endendend%solve the linear system of equationX=A\B;%reshape X to restore the output image% counter=0;% for x=1:size(map,1)% for y=1:size(map,2)% if im_mask(x,y)==1% counter=counter+1;% im_out(x,y,i)=X(counter);% end% end% endfor counter=1:length(X)[index_x,index_y]=find(map==counter);im_out(index_x,index_y,i)=X(counter);end%release allclear A B X lap_source lap_target g_mag_source g_mag_target end im_out=uint8(im_out); end

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