motionEstES.m

% Computes motion vectors using exhaustive search method
%
% Input
%   imgP : The image for which we want to find motion vectors
%   imgI : The reference image
%   mbSize : Size of the macroblock
%   p : Search parameter  (read literature to find what this means)
%
% Ouput
%   motionVect : the motion vectors for each integral macroblock in imgP
%   EScomputations: The average number of points searched for a macroblock
%
% Written by Aroh Barjatya

function [motionVect, EScomputations, time] = motionEstES(imgP, imgI, mbSize, p)
tic

imgI = double(imgI);
imgP = double(imgP);

[row, col] = size(imgI);

vectors = zeros(2, row * col / mbSize^2);
costs = ones(2*p + 1, 2*p +1) * 65537;

computations = 0;

% we start off from the top left of the image
% we will walk in steps of mbSize
% for every marcoblock that we look at we will look for
% a close match p pixels on the left, right, top and bottom of it

mbCount = 1;
for i = 1 : mbSize : row - mbSize + 1
    for j = 1 : mbSize : col - mbSize + 1
        
        % display the target macroblock
        imgP_rect = drawRectangle(imgP, [i, j], [i+mbSize-1, j+mbSize-1], 1, 255);
        subplot(1, 2, 1);
        imshow(uint8(imgP_rect), 'InitialMagnification', 'fit');
        title('Target Frame')
        
        img = double(imgI);
        color = 0;
        
        % the exhaustive search starts here
        % we will evaluate cost for  (2p + 1) blocks vertically
        % and (2p + 1) blocks horizontaly
        % m is row(vertical) index
        % n is col(horizontal) index
        % this means we are scanning in raster order
        
        for m = -p : p
            for n = -p : p
                refBlkVer = i + m;   % row/Vert co-ordinate for ref block
                refBlkHor = j + n;   % col/Horizontal co-ordinate
                if ( refBlkVer < 1 || refBlkVer+mbSize-1 > row ...
                        || refBlkHor < 1 || refBlkHor+mbSize-1 > col)
                    continue;
                end
                
                costs(m+p+1,n+p+1) = costFuncMAD(imgP(i:i+mbSize-1,j:j+mbSize-1), ...
                     imgI(refBlkVer:refBlkVer+mbSize-1, refBlkHor:refBlkHor+mbSize-1), mbSize);
                
                 computations = computations + 1;
                 
                % Display the searching macroblock
%                 imgI_rect = drawRectangle(imgI, [refBlkVer, refBlkHor], [refBlkVer+mbSize-1, refBlkHor+mbSize-1], 1, 255);
%                 subplot(1, 2, 2);
%                 imshow(uint8(imgI_rect), 'InitialMagnification', 'fit');
%                 title('Reference Frame');
%                 pause(0.1);
                % Display the searching macroblock
                
                img = drawRectangle(img, [refBlkVer, refBlkHor], [refBlkVer+mbSize-1, refBlkHor+mbSize-1], 1, color);
                color = color + 25;
                subplot(1, 2, 2);
                imshow(uint8(img), 'InitialMagnification', 'fit');
                title('Reference Frame');
                pause(0.5);

            end
        end
        
        % Now we find the vector where the cost is minimum
        % and store it ... this is what will be passed back.
        
        [dx, dy, ~] = minCost(costs);   % finds which macroblock in imgI gave us min Cost
        vectors(1, mbCount) = dy-p-1;    % row co-ordinate for the vector
        vectors(2, mbCount) = dx-p-1;    % col co-ordinate for the vector
        
        % display the selected macroblock
%         subplot(1, 2, 2);
%         imgI_rect = drawRectangle(imgI, [i+vectors(1, mbCount), j+vectors(2, mbCount)], [i+vectors(1, mbCount)+mbSize-1, j+vectors(2, mbCount)+mbSize-1], 1, 255);
%         imshow(uint8(imgI_rect), 'InitialMagnification', 'fit');
%         title('Reference Frame');
%         pause(0.5);
        
        mbCount = mbCount + 1;
        costs = ones(2*p + 1, 2*p +1) * 65537;
    end
end

motionVect = vectors;
EScomputations = computations/(mbCount - 1);
time = toc;
end