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HSV Averages and SD for Image Processing Toolbox

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Jacob Siahaan
Jacob Siahaan am 30 Apr. 2020
Kommentiert: Jacob Siahaan am 30 Apr. 2020
I am new to Matlab, it is only my first week. I am trying to calculate the average hue across all image pixels along with the standard deviation. Same applies to saturation and value.
My code is:
rgbImage = imread('001.jpg');
hsv = rgb2hsv(rgbImage);
h = hsv(:, :, 1); % Hue image.
s = hsv(:, :, 2); % Saturation image.
v = hsv(:, :, 3); % Value (intensity) image.
meanh = mean(h);
display(meanh)
My output shows columns, but I am seeking the average across all image pixels and to my understanding it seems like the table (for mean) shows average hue per pixel.

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Guillaume
Guillaume am 30 Apr. 2020
Bearbeitet: Guillaume am 30 Apr. 2020
mean like many functions in matlab operates along the first non-scalar dimension of a matrix. Your h is a 2D matrix, so the first non-scalar dimension is the rows and mean gives you the average across the rows (hence the average of each column).
If you're using a reasonably modern version of matlab (2018b or later) you can tell mean to operate across all the dimensions at once:
meanh = mean(h, 'all');
In older versions, you can either call mean twice:
meanh = mean(mean(h)); %first get the mean across the rows, then across the columns
but be careful that it doesn't work for non-linear functions such as std. Instead you can reshape your matrix so it has only one dimension:
meanh = mean(h(:)); %reshape into a column, then take the mean
or use the mean2 function which gives you the mean of all pixels of a 2D image:
meanh = mean2(h);
I recommend the first ('all' option) or 3rd option ( use (:)) for older versions.

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