Reduce allocated memory, speed up algorithm?, split matrix in "inequal" sized matrices?

Hello, I've the following task where I want to minimize the memory consumption (and also speed up). I've a matrix with rows of different height (varies about 1 pixel). Now I want to get about 80% of the center of the each block (which means ignoring the first 10% and last 10% of the block). The center of block is in the vector yc

I calculate the mean over the regions denoted with 1 in each block (I've about 50 blocks)

 0000000
 1111111
 1111111
 1111111 
 1111111
 1111111
 1111111
 1111111
 1111111
 0000000

When the blocksize would be exactly the same, each time I could you use blockproc with the following code fragment

 tic 
 row80centerproz = round(0.1*nPixOfRow):round(0.9*nPixOfRow);
 mean80FilterFunction = @(theBlockStructure) mean(theBlockStructure.data(row80centerproz,:));
 blockSize = [nPixOfRow 1];
 RowMW = blockproc(Imagenew, blockSize, mean80FilterFunction,'PadPartialBlocks',true,'PadMethod', 'replicate');
 t2 = toc;

but this would result in an increasing "shift" in the end I do not get the 80% in the middle, but 80% in the end or the beginning (depending if I create nPixOfRow with ceil or floor ) Here the peak and allocated memory is fine

at the moment I use

tic
for irow = 1:nrows
        tmpSubImg = SubImg2(ImageIN,round([1 yc(irow)-halfHeight, ImSize(2), height]));
        RowMW(irow,:)  = mean(tmpSubImg);
end
t1 = toc;

function subimg=SubImg2(img,rect)
ylo = max([1 rect(2)]);
yhi = min([size(img,1) rect(2)+rect(4)-1]);
xlo = max([1 rect(1)]);
xhi = min([size(img,2) rect(1)+rect(3)-1]);
subimg = img(ylo:yhi,xlo:xhi,:);
end

 There I've 21662772.00 Kb allocated memory 
 and a peak memory of 564400.00 Kb

Can I speed up the process with less memory allocation without using a loop, for example be reshaping the matrix into different sized matrix

tic RowMW = blockproc(Imagenew, blockSize, mean80FilterFunction,'PadPartialBlocks',true,'PadMethod', 'replicate'); t2 = toc;

Blockproc has an allocated memory of 540720.00 Kb and a peak memory of 528776.00 Kb ...

Is there a way to change my implemention to reduce the allocated memory (and even more to speed up the process?)

Thank you

Answer 1

[Prasad Mendu]

Refer to the links given below to get started on how to make efficient use of memory and increase code performance in MATLAB.

https://www.mathworks.com/help/matlab/matlab_prog/strategies-for-efficient-use-of-memory.html

https://www.mathworks.com/help/matlab/code-performance.html