hbma.m

以MATLAB做HBMA的碼源

function [totaltime,avgMBSearch,avgMAD,avgMSE,PSNR]=HBMA(Target_Img , Anchor_Img , Img_Height , Img_Width , BlockSize , rangs ,range , figureon) 
% 
%function [totaltime,avgMBSearch,avgMAD,avgMSE,PSNR]=HBMA(Target_Img,Anchor_Img,Img_Height,Img_Width,BlockSize,rangs,range,figureon) 
% 
%This function calculate block motion vectors (with integer pel accuracy), using hierarchical block matching algorithm. 
%An example of main function calling this function is "MEMBA", which can be entered on the command window. 
%The function also use the function "EBMA" for motion estimation of every macroblock 
% 
%	TargetName,AnchorName:  
%		File Names of Target Frame and Anchor Frame 
%	Img_Height,Img_Width:   
%		Image Height and Width of a Frame 
%  BlockSize:              
%		The size of Macro Block in Frame is BlockSize(1) by BlockSize(2) 
%	rangs,range:       
%		The Search Field in Frame A is from (rangs(1),rangs(2)) to (range(1),range(2)) 
%  Target_Img,Anchor_Img,Predict_Img: 
%		Image Matrix for Target Frame, Anchor Frame, Predicted Frame 
%	ox,oy,pxx,pyy: 
%		The location of Motion vector is (ox,oy), (pxx,pyy) for the direction  
%	PSNR: 
%		The peak signal and noise ratio between original image and predicted image 
%	L: 
%		The search level 
%	Author: Xiaofeng Xu, Polytechnic University  4/21/2002 
%   totaltime: 
%       The total time of ME algorithm execution between original and predicted images (platform depended) 
%   avgMBSearch: 
%        The average number of Macro Block matching stages between original and predicted images 
%   avgMAD: 
%       The average MAD between original and predicted images 
%   avgMSE: 
%       The average MSE between original and predicted images 
%   Author: Evgeny Kaminsky, Ben Gurion University 12/18/2002 
L=3; 
%Number of MB searches; 
c_MB_search=8; 
%Read images from files 
%fid = fopen(Target_Img,'r'); 
%Target_Img= fread(fid,[Img_Height,Img_Width]); 
%fclose(fid); 
Target_Img=double(Target_Img); 
 
%fid = fopen(Anchor_Img,'r'); 
%Anchor_Img= fread(fid,[Img_Height,Img_Width]); 
%fclose(fid); 
Anchor_Img=double(Anchor_Img); 
 

if (figureon) 
    %Display the results 
   figure; 
    imshow(uint8(Target_Img)); 
    title('Target Image')  
end 
t0 = clock; 
m=1; 
Factor=2.^(L-1); 
%Downsample Image with different resolution 
Up_Target_Img=zeros(Img_Height*2,Img_Width*2); 
Up_Target_Img(1:2:Img_Height*2,1:2:Img_Width*2)=Target_Img; 
Up_Target_Img(1:2:Img_Height*2-1,2:2:Img_Width*2-1)=(Target_Img(:,1:Img_Width-1)+Target_Img(:,2:Img_Width))/2; 
Up_Target_Img(2:2:Img_Height*2-1,1:2:Img_Width*2-1)=(Target_Img(1:Img_Height-1,:)+Target_Img(2:Img_Height,:))/2; 
Up_Target_Img(2:2:Img_Height*2-1,2:2:Img_Width*2-1)=(Target_Img(1:Img_Height-1,1:Img_Width-1)+Target_Img(1:Img_Height-1,2:Img_Width)+Target_Img(2:Img_Height,1:Img_Width-1)+Target_Img(2:Img_Height,2:Img_Width))/4; 
 
TargetDown=zeros(3,Img_Height,Img_Width); 
%AnchorDown=TargetDown; 
TargetDown1=Target_Img; 
AnchorDown1=Anchor_Img; 
 
AnchorDown2(1:Img_Height/2,1:Img_Width/2)=Anchor_Img(1:2:Img_Height,1:2:Img_Width); 
AnchorDown3(1:Img_Height/4,1:Img_Width/4)=AnchorDown2(1:2:Img_Height/2,1:2:Img_Width/2); 
 
TargetDown2(1:Img_Height/2,1:Img_Width/2)=Target_Img(1:2:Img_Height,1:2:Img_Width); 
TargetDown3(1:Img_Height/4,1:Img_Width/4)=TargetDown2(2:2:Img_Height/2,1:2:Img_Width/2); 
 
Predict_Img=Target_Img; 
 
rangs(1)=rangs(1)/Factor; 
range(1)=range(1)/Factor; 
 
rangs(2)=rangs(2)/Factor; 
range(2)=range(2)/Factor; 
 
Img_Height=Img_Height/Factor; 
Img_Width=Img_Width/Factor; 
 
 
%Search for all the blocks in Anchor Images of 1st level 
for i=1:BlockSize(1):Img_Height-BlockSize(1)+1 
   RangeStart(1)=i+rangs(1); 
   RangeEnd(1)=i+BlockSize(1)-1+range(1); 
   if RangeStart(1)<1 
      RangeStart(1)=1; 
   end    
   if RangeEnd(1)>Img_Height 
      RangeEnd(1)=Img_Height; 
   end 
   for j=1:BlockSize(2):Img_Width-BlockSize(2)+1 
      RangeStart(2)=j+rangs(2); 
      RangeEnd(2)=j+BlockSize(2)-1+range(2); 
	   if RangeStart(2)<1 
   	   RangeStart(2)=1; 
	   end    
   	if RangeEnd(2)>Img_Width 
      	RangeEnd(2)=Img_Width; 
      end 
      tmpt(:,:)=TargetDown3(:,:); 
      tmpa(:,:)=AnchorDown3(:,:); 
      [px(m), py(m),MB_search]=EBMA(tmpt,tmpa,BlockSize,[i,j],RangeStart,RangeEnd); 
      c_MB_search=MB_search+c_MB_search; 
      ox(m)=j; 
      oy(m)=i; 
      m=m+1; 
   end 
end 
if (figureon) 
%Disfplay the results 
    figure; 
    imshow(uint8(TargetDown3)); 
    title('TargetDown3') 
    figure; 
    imshow(uint8(AnchorDown3)); 
    title('AnchorDown3') 
 
    hold on 
    quiver(ox,oy,px,py); 
 
    hold off 
    axis image 
end 
%Search for all the blocks in Anchor Images of all levels 
for ii=L-1:-1:1 
   %Update all parameters for the currenet level. 
   px=px*2; 
   py=py*2; 
   Img_Height=Img_Height*2; 
   line_width=floor(Img_Width/BlockSize(2)); 
   Img_Width=Img_Width*2; 
   ttt=size(py); 
    
	 m=1; 
    %Search for all the blocks in Anchor Images in the iith level 
    for i=1:BlockSize(1):Img_Height-BlockSize(1)+1 
       
      baseline=double(uint32(i/2/BlockSize(1)))*double(line_width); 
      for j=1:BlockSize(2):Img_Width-BlockSize(2)+1 
         %Caculate the search range in Target Images. 
         mindx=floor(baseline+double(uint32(j/2/BlockSize(2)))+1); 
         if mindx>ttt(2) 
            mindx=ttt(2); 
         end 
          
         RangeStart(1)=i+py(mindx)+rangs(1); 
	   	RangeEnd(1)=i+py(mindx)+BlockSize(1)-1+range(1); 
	   	if RangeStart(1)<1 
   	   	RangeStart(1)=1; 
	   	end    
	   	if RangeEnd(1)>Img_Height 
   	   	RangeEnd(1)=Img_Height; 
	   	end 
          
         RangeStart(2)=j+px(mindx)+rangs(2); 
	      RangeEnd(2)=j+px(mindx)+BlockSize(2)-1+range(2);          
         if RangeStart(2)<1 
   		   RangeStart(2)=1; 
		   end    
   		if RangeEnd(2)>Img_Width 
      		RangeEnd(2)=Img_Width; 
         end 
          
         if ii==2 
      	     tmpt=TargetDown2(:,:); 
              tmpa=AnchorDown2(:,:); 
               
         end  
            
         if ii==1 
      	     tmpt=TargetDown1(:,:); 
              tmpa=AnchorDown1(:,:); 
               
          end 
           
			    [pxx(m), pyy(m),MB_search, Predict_Img(i:i+BlockSize(1)-1,j:j+BlockSize(1)-1)]=EBMA(tmpt,tmpa,BlockSize,[i,j],RangeStart,RangeEnd); 
                c_MB_search=MB_search+c_MB_search; 
  
                  %Refine final result by half-pel accuracy search    
         if(ii==1)                   
            RangeStart(1)=(i+pyy(m))*2-1-2; 
	  		 	RangeEnd(1)=(i+pyy(m))*2-1+BlockSize(1)*2-1+2; 
	   		if RangeStart(1)<1 
   	   		RangeStart(1)=1; 
		   	end    
		   	if RangeEnd(1)>Img_Height*2 
   		   	RangeEnd(1)=Img_Height*2; 
	   		end 
          
         	RangeStart(2)=(j+pxx(m))*2-1-2; 
		      RangeEnd(2)=(j+pxx(m))*2-1+BlockSize(2)*2-1+2;          
   	      if RangeStart(2)<1 
   			   RangeStart(2)=1; 
		   	end    
            if RangeEnd(2)>Img_Width*2 
               RangeEnd(2)=Img_Width*2; 
      	   end 
	  	      tmpa=AnchorDown1(:,:); 
                [pxx(m), pyy(m),MB_search,Predict_Img(i:i+BlockSize(1)-1,j:j+BlockSize(1)-1)]=EBMA(Up_Target_Img,tmpa,BlockSize,[i,j],RangeStart,RangeEnd,2); 
               c_MB_search=MB_search+c_MB_search; 
   	  end 
	     	ox(m)=j; 
	      oy(m)=i; 
      	m=m+1; 
	  end 
	end 
   px=pxx; 
   py=pyy; 
    
end 
totaltime=etime(clock,t0); 
imgsize = Img_Height*Img_Width; 
%Caculate error image 
Error_Img=Anchor_Img-Predict_Img; 
%Calculate totalerror 
totalerror=sum(sum(abs(Error_Img))); 
%Calculate average MAD 
avgMAD=totalerror/imgsize; 
%Calculate average MSE 
avgMSE=mean(mean((Error_Img.^2))); 
%Caculate PSNR 
PSNR=10*log10(255*255/avgMSE); 
%Claculate average number of searching stages for each Macro Block 
MB_total=imgsize/(BlockSize(1)*BlockSize(2)); 
avgMBSearch = c_MB_search/MB_total; 
 
 
if (figureon) 
     
%Display the results 
figure; 
imshow(uint8(TargetDown2)); 
title('TargetDown2') 
figure; 
imshow(uint8(AnchorDown2)); 
%imshow(AnchorDown2); 
title('AnchorDown2') 
hold on 
quiver(ox,oy,pxx,pyy); 
 
hold off 
pause(2); 
 
%Display the results 
figure; 
imshow(uint8(Anchor_Img)); 
title('Anchor Image') 
 
hold on 
quiver(ox,oy,pxx,pyy); 
 
hold off 
axis image 
 
figure; 
imshow(uint8(Predict_Img)); 
title('Predicted Image') 
 
figure; 
imshow(uint8(Error_Img)); 
title('Error Image') 
end