CODEWITHSUNDEEP
matlab
Chethan S.
Chethan S.

Reputation: 556

nlfilter taking same values twice

I used nlfilter for a test function of mine as follows:

function funct
clear all;
clc;
I = rand(11,11);
ld = input('Enter the lag = ') % prompt for lag distance
A = nlfilter(I, [7 7], @dirvar);

% Subfunction
    function [h] = dirvar(I)
        c = (size(I)+1)/2
        EW = I(c(1),c(2):end)
        h = length(EW) - ld
    end
end

The function works fine but it is expected that nlfilter progresses element by element, but in first two iterations the values of EW will be same 0.2089 0.4162 0.9398 0.1058. But then onwards for all iterations the next element is selected, for 3rd it is 0.4162 0.9398 0.1058 0.1920, for 4th it is 0.9398 0.1058 0.1920 0.5201 and so on. Why is it so?

Upvotes: 1

Views: 611

Answers (2)

Egon
Egon

Reputation: 4787

I hope you know what the length function does? It does not give you the Euclidean length of a vector, but rather the largest dimension of a vector (so in your case, that should be 4). If you want the Euclidean length (or 2-norm), use the function norm instead. If your code does the right thing, you might want to use something like:

sz = size(I,2);
h = sz - (sz+1)/2 - ld;

In your example, this means that depending on the lag you provide, the output should be constant. Also note that you might want to put semicolons after each line in your subfunction and that using clear all as the first line of a function is useless since a function will always be executed in its own workspace (that will however clear persistent or global variables, but you don't use them in your code).

Upvotes: 0

Ghaul
Ghaul

Reputation: 3330

This is nothing to worry about. It happens because nlfilter needs to evaluate your function to know what kind of output to create. So it uses feval once before starting to move across the image. The output from this feval call is what you see the first time.

From the nlfilter code:

% Find out what output type to make.
rows = 0:(nhood(1)-1);
cols = 0:(nhood(2)-1);
b = mkconstarray(class(feval(fun,aa(1+rows,1+cols),params{:})), 0, size(a));

% Apply fun to each neighborhood of a
f = waitbar(0,'Applying neighborhood operation...');
for i=1:ma,
    for j=1:na,
        x = aa(i+rows,j+cols);
        b(i,j) = feval(fun,x,params{:});
    end
    waitbar(i/ma)
end

The 4th line call to eval is what you observe as the first output from EW, but it is not used to anything other than making the b matrix the right class. All the proper iterations happen in the for loop below. This means that the "duplicate" values you observe does not affect your final output matrix, and you need not worry.

Upvotes: 1

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