How to make a diagonal divider of zeros and ones u

问题:

This is the result that I want. The number of bits resolution are 256 x 256.

// assign default background to white.
img = ones(256, 256);

Example Result:

0 1 1 1
0 0 1 1
0 0 0 1
0 0 0 0

Is there a way that I can use the zeros() and ones() function in MATLAB to achieve this result? How should I do the looping?

The result is something that eye() function can do, but it only do a diagonal lines. I want a diagonal lines that separate zeros and ones.

回答1:

You are looking for the triu function

img = triu( ones( 256 ), 1 );

回答2:

If you care about performance, you can try a bsxfun based method -

n = 256; %// resolution of img would be nxn
img = bsxfun(@le,[1:n]',0:n-1);

---

Benchmarks comparing BSXFUN and TRIU -

num_runs = 50000; %// Number of iterations to run benchmarks
n =  256; %// nxn would be the resolution of image

%// Warm up tic/toc.
for k = 1:50000
    tic(); elapsed = toc();
end

disp(['For n = ' num2str(n) ' :'])
disp('---------------------- With bsxfun')
tic
for iter = 1:num_runs
    out1 = bsxfun(@le,[1:n]',0:n-1); %//'
end
time1 = toc;
disp(['Avg. elapsed time = ' num2str(time1/num_runs) ' sec(s)']),clear out1

disp('---------------------- With triu')
tic
for iter = 1:num_runs
    out2 = triu( true( n ), 1 );
end
time2 = toc;
disp(['Avg. elapsed time = ' num2str(time2/num_runs) ' sec(s)']),clear out2

Results

For n = 256 :
---------------------- With bsxfun
Avg. elapsed time = 0.0001506 sec(s)
---------------------- With triu
Avg. elapsed time = 4.3082e-05 sec(s)

For n = 512 :
---------------------- With bsxfun
Avg. elapsed time = 0.00035545 sec(s)
---------------------- With triu
Avg. elapsed time = 0.00015582 sec(s)

For n = 1000 :
---------------------- With bsxfun
Avg. elapsed time = 0.0015711 sec(s)
---------------------- With triu
Avg. elapsed time = 0.0019307 sec(s)

For n = 2000 :
---------------------- With bsxfun
Avg. elapsed time = 0.0058759 sec(s)
---------------------- With triu
Avg. elapsed time = 0.0083544 sec(s)

For n = 3000 :
---------------------- With bsxfun
Avg. elapsed time = 0.01321 sec(s)
---------------------- With triu
Avg. elapsed time = 0.018275 sec(s)

Conclusions from benchmarks

For your 256x256 sized problem, triu might be the preferred approach, but for decently big enough datasizes, one can look into bsxfun for upto 50% performance improvement.