How to divide a 2d array into blocks and create an array with the mean value of each block?
11 visualizaciones (últimos 30 días)
Mostrar comentarios más antiguos
Steve Francis
el 26 de Mayo de 2022
Comentada: Jan
el 27 de Mayo de 2022
Here's an 4x8 array.Three of its values are NaNs:
B=zeros(4,8);
B(1,:) = [1 3 4 3 10 0 3 4];
B(2,:) = [5 7 2 NaN 8 2 3 4];
B(3,:) = [8 4 6 2 NaN 3 5 7];
B(4,:) = [2 2 5 5 1 NaN 4 4];
I want to divide the array into 2x2 blocks and form a new array 'C' that is the mean of each block. If the block contains one or more NaNs, I want to find the average of the numbers that are not NaNs. In this example, I would like the following output:
C =
4.0000 3.0000 5.0000 3.5000
4.0000 4.5000 2.0000 5.0000
I tried the code below but it just returns a NaN if any of the block elements are NaN. How should I amend this, please?
C=blockproc(B, [2 2], @(block_struct) mean(block_struct.data(:)))
C =
4.0000 NaN 5.0000 3.5000
4.0000 4.5000 NaN 5.0000
0 comentarios
Respuesta aceptada
Jan
el 26 de Mayo de 2022
Editada: Jan
el 26 de Mayo de 2022
B = [1 3 4 3 10 0 3 4; ...
5 7 2 NaN 8 2 3 4; ...
8 4 6 2 NaN 3 5 7; ...
2 2 5 5 1 NaN 4 4];
B = repmat(reshape(B, 1, 4, 8), 10, 1, 1); % The test data
% Code without BLOCKPROC:
N = ~isnan(B); % Mask for the NaNs
S = size(B);
T = [S(1), 2, S(2)/2, 2, S(3)/2];
BB = reshape(B .* N, T); % Set NaNs to 0
NN = reshape(N, T);
R = sum(BB, [2, 4]) ./ sum(NN, [2, 4]); % Sum over 2x2 blocks
R = reshape(R, T([1,3,5])); % Remove singelton dimensions
2 comentarios
Jan
el 27 de Mayo de 2022
You are welcome. I do not have the image processing toolbox, so I use solutions without blockproc.
The method shown above is fast and more flexibel, if the inputs are no 2D or 3D RGB arrays and the blocks are built on the 1st 2 dmensions. Instead of ~isnan() other masks can be defined. blockproc is more powerful, when specific functions are applied to the blocks, but power costs processing time.
See also: https://www.mathworks.com/matlabcentral/fileexchange/24812-blockmean (no masking of NaNs impelemented, frist 2 dimensions processed also, dimensions do not need to be a multiple of the window size)
Más respuestas (1)
David Hill
el 26 de Mayo de 2022
C=blockproc(B, [2 2], @(block_struct) mean(block_struct.data(:),'omitnan'))
2 comentarios
Ver también
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!