Hey Areej,
I understand that you are doing image processing in which you want to:
- Sample the scanned row into 100 equidistant samples.
- Quantize the sampled image using 8 quantization levels.
Assuming you want to do this in MATLAB, here is the possible solution:
For sampling the scanned row into 100 equidistant samples, you can use the “linspace” function. Example code for reference:
% Assuming you have the scanned row image stored in a variable called 'rowImage
% Calculate the width of the scanned row images
width = size(rowImage, 2);
% Sample the image into 100 equidistant samples
numSamples = 100;
sampledIndices = round(linspace(1, width, numSamples));
% Extract the sampled values from the row image
sampledValues = rowImage(:, sampledIndices);
To quantize the sampled image into 8 quantization levels, you can use the “quantiz” function. Example code for reference:
% Assuming you have the sampled values stored in a variable called 'sampledValues'
% Determine the minimum and maximum values in the sampled image
minValue = min(sampledValues(:));
maxValue = max(sampledValues(:));
% Calculate the interval width for each quantization level
intervalWidth = (maxValue - minValue) / 8;
% Quantize the sampled values
quantizedValues = quantiz(sampledValues, minValue:intervalWidth:maxValue);
Hope this helps!
