Exhaustive Block Matching Algorithm

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Hi all,

I'm trying to write the Exhaustive Block Matching Algorithm based on the pseudo-code written in this slide: http://inst.eecs.berkeley.edu/~ee290t/sp04/lectures/motion_estimation.pdf

I think I wrote my programme not correctly but don't know where I was wrong. Can anyone please help me? Thank you very much :(

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Jan 2012-2-1

It is very likely, that someone is assisting to solve the problems if you post the corresponding code and explain, what's going wrong. Currently the best answer is: "yes".

lianjiang 2022-11-15

请问还有其他的pdf可以分享一下吗

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Answer 1

Qihan Gao 2021-8-29

在 MATLAB Online 中打开

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Hi, a reply after nearly 10 years to the original question. Since I am learning this subject these days, I have modified the codes to get it work. Here are my modified codes.

%Extract the matrix of your image and doing rgb2ycbcr transformation
%Here we assume that the Y_ref and Y_predict are the Luminance plane matrix
%As in YCbCr/YUV dimension, 
%Cb and Cr carries less information that human sensors hard to detect
%Y_ref is the original first frame
%Y_predict is the original second frame
%N is the macroblock size
%R is the radius of pixels of the searching window
%Y_esitimate is the new second frame that the function produces from
%original first frame
%SAD is Sum of Absolute Difference
%Reson of using SAD not MAD is considering the total arithmetic operations
%Using SAD can reduce the computional complexity comparing to calculating MAD
function [Y_estimate SAD_counter] = Exhaustive_Search(Y_ref,Y_predict,N,R)
%SAD operations conunter
SAD_counter = 0;
[height width] = size(Y_ref);
for i = 1:N:height-N+1
    for j = 1:N:width-N+1
        %initialisation of SAD_min, the maximum value is 1xN^2 (after scaling)
        SAD_min = 1*N^2;
        for m = -R:1:R
            for n = -R:1:R    
                if ( i+m < 1 || i+m+N-1 > height || j+n < 1 || j+n+N-1 > width)  
                    continue;
                end
                SAD=sum(abs(Y_predict(i:i+N-1,j:j+N-1)-Y_ref(i+m:i+m+N-1,j+n:j+n+N-1)),'all');
                SAD_counter = SAD_counter+1;
                if (SAD < SAD_min)
                   SAD_min = SAD; Y_estimate(i:i+N-1,j:j+N-1) = Y_ref(i+m:i+m+N-1,j+n:j+n+N-1);
                end
            end
        end
    end
end

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Answer 2

Walter Roberson 2012-2-1

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On one of the lines, you have a typing mistake.

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Tuan Nguyen 2012-2-7

I'm sorry about that since my English is not so good.

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Answer 3

Tuan Nguyen 2012-2-7

在 MATLAB Online 中打开

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Oh I'm so sorry for forgetting posting my code. This is my matlab code written for exhaustive block matching algorithm

function motionVect = motionEst(f1,f2,N,R)
[height width] = size(f2);
figure,imshow(f2);
hold on;
for i = 1:N:height-N
    for j = 1:N:width-N
        MAD_min = 256;
        mvx = 0;
        mvy = 0;
        for k = -R:1:R
            for l = -R:1:R
                %MAD=sum(sum(abs(f1(i:i+N-1,j:j+N-1)-f2(i+k:i+k+N-1,j+l:j+l+N-1))));
                MAD = 0;
                for u = i:i+N-1
                    for v = j:j+N-1
                        if ((u+k > 0)&&(u+k < height + 1)&&(v+l > 0)&&(v+l < width + 1))
                            MAD = MAD + abs(f1(u,v)-f2(u+k,v+l));
                        end
                    end
                end
        MAD = MAD/(N*N);
                if (MAD<MAD_min)
                    MAD_min = MAD;
                    dy = k;
                    dx = l;
                end
            end
        end
        iblk = floor((i-1)/(N+1))+1;
        jblk = floor((j-1)/(N+1))+1;
        mvx(iblk,jblk) = dx;
        mvy(iblk,jblk) = dy;
        %figure, imshow(f2);
        %hold on;
        arrow([i j],[i+dy j+dx], 3);
    
    end
end