motion estimation almost finished

Author: yolanda93

Motion-Estimation/Block_Matching.m

@@ -1,36 +1,52 @@
 function [ x_predicted, y_predicted, min_MSE ] = Block_Matching( reference_frame, new_frame, p, x, y, block_size  )
-%Block_Matching Algorithm. Block Matching between 2 subsequent frames to detect motion estimation
-%   reference_frame   The frame{t-1}
-%   new_frame         The frame{t}
-%   p                 Search parameter
-%   x,y               Position withing the frame
-%   block_size        Size of the macroblock
+% Block_Matching Algorithm. Block Matching between 2 subsequent frames to detect motion estimation
+%
+% Input
+%   reference_frame :  The frame{t-1}
+%   new_frame       :  The frame{t}
+%   p               :  Search parameter
+%   x,y             :  Position withing the frame
+%   block_size      :  Size of the macroblock
+% 
+% Ouput 
+%   motion_vect     :  Motion vector for each macroblock
+%   min_MSE         :  The minimum MSE (Mean Square Error)
+% 
 
-reference_block = reference_frame(x:x+block_size,y:y+block_size,:);
-MSE = zeros(p,p);
+reference_block = reference_frame(x:x+(block_size-1),y:y+(block_size-1));
+MSE = ones(2*p + 1, 2*p +1) * 65537;
 
-for new_xpos=x-p:1:x+(p-1)
-    for new_ypos=y-p:1:y+(p-1)
-        if(new_xpos+block_size>size(reference_frame,1) || new_ypos+block_size>size(reference_frame,2) || new_xpos<=0 || new_ypos<=0)
-          MSE(new_xpos-(x-p)+1,new_ypos-(y-p)+1)=1000;
+% Search the correspondence of the macroblock of a reference frame
+% using an exhaustive method. This method searches for the minimum
+% cost function at each possible location with respect to the search parameter.
+
+for m=-p:p
+    for n=-p:p
+        new_xpos = x + m;
+        new_ypos = y + n;
+        if(new_xpos+block_size>size(reference_frame,1) || new_ypos+block_size>size(reference_frame,2) || new_xpos<1 || new_ypos<1)
+            continue;
         else
-          new_block =new_frame(new_xpos:new_xpos+block_size,new_ypos:new_ypos+block_size,:);
-          MSE(new_xpos-(x-p)+1,new_ypos-(y-p)+1)=double(mean2(((reference_block-new_block).^2)));
+            new_block =new_frame(new_xpos:new_xpos+(block_size-1),new_ypos:new_ypos+(block_size-1));
+            MSE(m+p+1,n+p+1)=double(mean2(((reference_block-new_block).^2)));
         end
     end
 end
 
-min_MSE = min(min(MSE));
-
-[min_x,min_y]=find(min_MSE);
+% Create the motion vectors with the minimum cost function.
+min = 70000;
+for i = 1:size(MSE,1)
+    for j = 1:size(MSE,2)
+        if (MSE(i,j) < min)
+            min = MSE(i,j);
+            dx = j; dy = i;
+        end
+    end
+end
 
-if(isempty(min_x)&&isempty(min_y)) % no movement detected
- x_predicted = x;
- y_predicted = y;
-else
-  x_predicted = min_x+(x-p);
- y_predicted = min_y+(y-p);
-end    
+min_MSE = min;
+x_predicted = dx;
+y_predicted = dy;
 
 end
 

Motion-Estimation/Motion_Compensation.m

@@ -0,0 +1,34 @@
+function  estimated_image = Motion_Compensation( reference_frame, motion_vect, block_size)
+%Motion_Compensation algorithm. Predicts the next image using the motion
+%vectors
+%   
+%  Input 
+%   reference_frame  : The frame{t-1} 
+%   motion_vect      : The motion vectors for each macroblock 
+%   block_size       : Size of the macroblock
+%
+%  Output
+%   estimated_image  : Result of using the motion vectors to predict a frame in a video stream
+%
+
+[row, col] = size(reference_frame);
+vect_count = 1;
+image_compensation = reference_frame;
+
+for i = 1:block_size:row-block_size
+    for j = 1:block_size:col-block_size        
+        dy = motion_vect(1,vect_count);
+        dx = motion_vect(2,vect_count);
+        y_block = i + dy;
+        x_block = j + dx;
+        if(y_block>=1&&x_block>=1&&dy~=0&&dx~=0)      
+            image_compensation(i:i+block_size-1,j:j+block_size-1) = reference_frame(y_block:y_block+block_size-1, x_block:x_block+block_size-1);
+        end
+        vect_count = vect_count + 1;
+    end
+end
+
+estimated_image = image_compensation;
+
+end
+

Motion-Estimation/Motion_Estimation.m

@@ -0,0 +1,28 @@
+function motion_vectors = Motion_Estimation(reference_frame, new_frame, block_size, p)
+%Motion_Estimation algorithm  Computes motion vectors using exhaustive search method
+%
+% Input
+%   reference_frame : The frame{t-1} 
+%   new_frame       : The frame{t}
+%   p               : Search parameter
+%   block_size      : Size of the macroblock
+%
+% Ouput
+%   motion_vectors  : The motion vectors for each macroblock 
+%
+
+[rows, cols] = size(reference_frame);
+motion_vectors = zeros(3,rows*cols/block_size^2);
+
+vect_count = 1;
+for posx = 1:block_size:rows-block_size
+    for posy = 1:block_size:cols-block_size
+          [predicted_posx,predicted_posy,min_MSE]=Block_Matching( reference_frame, new_frame, p, posx, posy, block_size  );
+          motion_vectors(1:2,vect_count) = [predicted_posx,predicted_posy];
+          motion_vectors(3,vect_count) = min_MSE;
+          vect_count = vect_count+1;
+    end
+end
+
+end
+