edit-error in calculating dsit

I have the matrices as below

A1=Ds(121:140, 121:140, 1:7)

A2=Ds(121:140, 121:140,7)

plz tell how to find the euclidean distance ,like in my previous post

Answer 1

[Junaid]

Well I guess you want to get single scalar value as distance of A2 for each Chanel in A1. If so then I try to do in steps. There are multiple ways but I would do like this.

First i will make A2 as single column vector

n_A2 = A2(:);

then I will make one matrix by A1, where each column is one image.

n_A1 = zeros(length(n_A2), size(A1,3)); % this creates matrix of rows as length of and columns are equal to number of images in A1

for i=1:size(A1,3)
   t= A1(:,:,i);
   n_A1(:,i) = t(:);
end

and Finally now compute the Euclidean distance n_A2 with all images in n_A1

A= repmat(n_A2,1,size(n_A1,2));
E_distance = sqrt(sum((A-n_A1).^2));

Now E_distance contains the output distance. There must be one value 0 as you are taking query image from the same pool of images.

I wish it works for you. I executed this on small example. Once you get A1 and A2 from Ds. then copy paste the following code below. It is the same code written above.

n_A2 = A2(:);
n_A1 = zeros(length(n_A2), size(A1,3));

for i=1:size(A1,3)
   t= A1(:,:,i);
   n_A1(:,i) = t(:);
end

A= repmat(n_A2,1,size(n_A1,2));
E_distance = sqrt(sum((A-n_A1).^2));

Answer 2

[Junaid]

Could you please tell what is Ds ? for simplicity make Ds random matrix and then simplify your questions.

[kash]

DS is an 3d image like cube ,formed from 2d slice