Hi all ,,,
I have matrix U=124 x 7
I want to find the mean through all 4 rows of each column
the result be 31 x7
MATLAB: Find mean for each 4 row in 124×7 matrix
mean through rows
Related Solutions
See this demo. It will be very easy for you to adapt it. Basically you do this:
meanFilterFunction = @(theBlockStructure) mean2(theBlockStructure.data(:)) * ones(2,2, class(theBlockStructure.data));blockSize = [32 32];blockyImage = blockproc(grayImage, blockSize, meanFilterFunction);Here's the full demo:
% Demo code to divide the image up into 16 pixel by 16 pixel blocks
% and replace each pixel in the block by the median, mean, or standard
% deviation of all the gray levels of the pixels in the block.
%
clc;clearvars;close all;workspace;fontSize = 16;% Read in a standard MATLAB gray scale demo image.
folder = fullfile(matlabroot, '\toolbox\images\imdemos');if ~exist(folder, 'dir') % If that folder does not exist, don't use a folder
% and hope it can find the image on the search path.
folder = [];endbaseFileName = 'cameraman.tif';fullFileName = fullfile(folder, baseFileName);grayImage = imread(fullFileName);% Get the dimensions of the image. numberOfColorBands should be = 1.
[rows columns numberOfColorBands] = size(grayImage)% Display the original gray scale image.
subplot(2, 2, 1);imshow(grayImage, []);title('Original Grayscale Image', 'FontSize', fontSize);% Enlarge figure to full screen.
set(gcf, 'Position', get(0,'Screensize')); set(gcf,'name','Image Analysis Demo','numbertitle','off') % Define the function that we will apply to each block.
% First in this demo we will take the median gray value in the block
% and create an equal size block where all pixels have the median value.
% Image will be the same size since we are using ones() and so for each block
% there will be a block of 8 by 8 output pixels.
medianFilterFunction = @(theBlockStructure) median(theBlockStructure.data(:)) * ones(size(theBlockStructure.data), class(theBlockStructure.data));% Block process the image to replace every pixel in the
% 8 pixel by 8 pixel block by the median of the pixels in the block.
blockSize = [8 8];% Quirk: must cast grayImage to single or double for it to work with median().
% blockyImage8 = blockproc(grayImage, blockSize, medianFilterFunction); % Doesn't work.
blockyImage8 = blockproc(single(grayImage), blockSize, medianFilterFunction); % Works.
[rows columns] = size(blockyImage8);% Display the block median image.
subplot(2, 2, 2);imshow(blockyImage8, []);caption = sprintf('Block Median Image\n32 blocks. Input block size = 8, output block size = 8\n%d rows by %d columns', rows, columns);title(caption, 'FontSize', fontSize);% Block process the image to replace every pixel in the % 4 pixel by 4 pixel block by the mean of the pixels in the block.
% The image is 256 pixels across which will give 256/4 = 64 blocks.
% Note that the size of the output block (2 by 2) does not need to be the size of the input block!
% Image will be the 128 x 128 since we are using ones(2, 2) and so for each of the 64 blocks across
% there will be a block of 2 by 2 output pixels, giving an output size of 64*2 = 128.
% We will still have 64 blocks across but each block will only be 2 output pixels across,
% even though we moved in steps of 4 pixels across the input image.
meanFilterFunction = @(theBlockStructure) mean2(theBlockStructure.data(:)) * ones(2,2, class(theBlockStructure.data));blockSize = [4 4];blockyImage64 = blockproc(grayImage, blockSize, meanFilterFunction);[rows columns] = size(blockyImage64);% Display the block mean image.
subplot(2, 2, 3);imshow(blockyImage64, []);caption = sprintf('Block Mean Image\n64 blocks. Input block size = 4, output block size = 2\n%d rows by %d columns', rows, columns);title(caption, 'FontSize', fontSize);% Block process the image to replace every pixel in the % 8 pixel by 8 pixel block by the standard deviation
% of the pixels in the block.
% Image will be smaller since we are not using ones() and so for each block
% there will be just one output pixel, not a block of 8 by 8 output pixels.
blockSize = [8 8];StDevFilterFunction = @(theBlockStructure) std(double(theBlockStructure.data(:)));blockyImageSD = blockproc(grayImage, blockSize, StDevFilterFunction);[rows columns] = size(blockyImageSD);% Display the block standard deviation filtered image.
subplot(2, 2, 4);imshow(blockyImageSD, []);title('Standard Deviation Filtered Image', 'FontSize', fontSize);caption = sprintf('Block Standard Deviation Filtered Image\n32 blocks. Input block size = 8, output block size = 1\n%d rows by %d columns', rows, columns);title(caption, 'FontSize', fontSize);sri, simply use blockproc():
% Uses blockproc() to get mean, median, and standard deviation of image blocks.
% Demo code to divide the image up into 4 pixel by 4 pixel blocks
% and replace each pixel in the block by the mean,
% of all the gray levels of the pixels in the block.
%
clc;clearvars;close all;workspace;fontSize = 16;% Read in a standard MATLAB gray scale demo image.
folder = fileparts(which('cameraman.tif'));if ~exist(folder, 'dir') % If that folder does not exist, don't use a folder
% and hope it can find the image on the search path.
folder = [];endbaseFileName = 'cameraman.tif';fullFileName = fullfile(folder, baseFileName);grayImage = imread(fullFileName);% Get the dimensions of the image. numberOfColorBands should be = 1.
[rows, columns, numberOfColorBands] = size(grayImage)% Display the original gray scale image.
subplot(1, 2, 1);imshow(grayImage, []);axis on;caption = sprintf('Original Grayscale Image\n%d rows by %d columns', rows, columns);title(caption, 'FontSize', fontSize);% Enlarge figure to full screen.
set(gcf, 'Position', get(0,'Screensize')); set(gcf,'name','Image Analysis Demo','numbertitle','off') % Define the function that we will apply to each block.
% First in this demo we will take the mean gray value in the block
% and create an pixel where all pixels have the mean value.
meanFilterFunction = @(theBlockStructure) mean2(theBlockStructure.data(:));% Block process the image to replace every pixel in the
% 4 pixel by 4 pixel block by the mean of the pixels in the block.
% The image is 256 pixels across which will give 256/4 = 64 blocks.
% Image will be the 1/4 the size of the original.
blockSize = [4 4];blockMeanImage = blockproc(grayImage, blockSize, meanFilterFunction);[rows, columns] = size(blockMeanImage);% Display the block mean image.
subplot(1, 2, 2);imshow(blockMeanImage, []);axis on;caption = sprintf('Block Mean Image\n64 blocks. Input block size = 4\n%d rows by %d columns', rows, columns);title(caption, 'FontSize', fontSize);% Get the first 8 mean values going across columns
first8Means = blockMeanImage(1, 1:8)message = sprintf('%.2f\n ', first8Means);message = sprintf('The first 8 means = \n%s\n', message)uiwait(helpdlg(message));
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