In Octave we can multiply every element of a matrix by a scalar using the .* operator
A=[1,2,3;
4,5,6];
B=A.*2
In general .* supports any two arguments of the same size.
C=A .* [2,2,2; 2,2,2]
It turns out these are actually the same operation, since Octave converts the first into the second via broadcasting
Quoting from the Octave docs, for element-wise binary operators and functions
The rule is that corresponding array dimensions must either be equal, or one of them must be 1.
In the case where one if the dimensions is 1, the smaller matrix is
tiled to match the dimensions of the larger matrix.
Here's another example you can try.
x = [1 2 3;
4 5 6;
7 8 9];
y = [10 20 30];
x + y
One potentially surprising aspect of Octave arrays is that the number
of dimensions is independent from the number of elements. We can add
as many dimensions as we like, as long as the only possible index in
those dimensions is 1. This can be particularly useful when trying
to broadcast with higher dimensional arrays.
ones(3,3,3) .* reshape([1,2,3],[1,1,3])
ones(3,3,3) .* reshape([1,2,3],[1,3,1])
Complete the following function. You may want to copy the definitions of A and B into the REPL
to understand the use of cat.
## usage: scale_layers(array, weights)
##
## multiply each layer of a 3D array by the corresponding weight
function out = scale_layers(array, weights)
out =
endfunction
%!test
%! onez = ones(3,3);
%! A=cat(3,onez, 2*onez, 3*onez);
%! B=cat(3,onez, 6*onez, 15*onez);
%! assert(scale_layers(A,[1;3;5]),B)
Save the image above left as
~/cs2613/labs/L21/paris.jpg (make sure you get the
full resolution image, and not the thumbnail).
Run the following demo code; you can change the weight vector for different colourization.
paris=imread("paris.jpg");
sepia=scale_layers(paris,[0.9,0.62,0.34]);
imshow(sepia);
You should get something like the following
Either for creative reasons, or as part of a more complex image processing task, it is common to convert images to monochrome.
Save the following image as
~/cs2613/labs/L21/owl.jpg (make sure you get the full resolution image, and not the thumbnail).
Complete the following function using scale_layers.
function out = monochrome(in, weights=[0.21,0.72,0.07])
out =
endfunction
Run the monochrome function on owl.jpg, you should get something like the following.
Try a few different values of weight vectors, see if you can generalize some rules from your experiments.
One useful operation on images is to detect how they are changing
locally. Roughly speaking the gradient can be thought about as
specifying both how much the intensity is changing, and what
direction that change is happening in. Octave returns that
information as an (x,y) vector in the usual parallel array way.
A = [0,0,0,0,0,1;
0,1,1,1,0,0;
0,1,1,1,0,1;
0,1,1,1,1,0;
0,1,1,1,1,0;
0,0,0,0,0,0];
[Dx, Dy] = gradient(A);
imshow(A);
figure;
imshow(Dx);
figure;
imshow(Dy);
Complete the follow function, by combining the Dx and Dy arrays
into a single array such that normimg(i,j) = norm([Dx(i,j),Dy(i,j)]). Don't use a loop. The demo should produce an
image somewhat like the one below.
function normimg = normgrad(img)
[Dx, Dy] = gradient(img);
normimg =
endfunction
%!demo
%! owl=imread("owl.jpg");
%! monowl=monochrome(owl);
%! ng = normgrad(monowl);
%! imshow(ng*2, [0,20]);
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