Blockproc for 2 functions (mean/std) slower then manuel splitting of the matrix?

Hello,

I try to optimize the processing speed and memory consumption of calculation some operations at different submatrices.

I tried the following versions:

Imagenew = Image(ys(1):ys(end),:);
meanFilterFunction = @(theBlockStructure) mean(theBlockStructure.data);
featureExtractionFunction = @(theBlockStructure) featureExtraction(theBlockStructure.data);

blockSize = [round(size(Imagenew,1)/nrows) 1];

tic
blockyImage_mean = blockproc(Imagenew, blockSize, meanFilterFunction);
t2=toc;
disp(['t2: ' num2str(t2)]);
disp(size(blockyImage_mean));

tic
blockyImage_feature = blockproc(Imagenew, blockSize, featureExtractionFunction);
t3=toc;
disp(['t3: ' num2str(t3)]);
disp(size(blockyImage_feature));

tic
for irow = 1:nrows
    for iChan = 1:nChan        
        tmpSubImg = SubImg2(Image(:,:,iChan),round([1 yc(irow)-halfHeight, ImSize(2), height]),0);
        RowMW(irow,:,iChan)  = mean(tmpSubImg);       % Mittelwert Zeile
        RowSTD(irow,:,iChan)  = std(tmpSubImg);       % Mittelwert Zeile
    end
end
t4=toc;
disp(['t4: ' num2str(t4)]);

function features = featureExtraction(Image) features(:,:,1) = mean(Image); features(:,:,2) = std(Image); end

and got the following results: t2: 5.0098 38 5601

t3: 12.0232 38 5601 2

t4: 6.8221

So my the blockproc function (calculating mean and std) seems to need twice the time than only calculating the mean, and even more then using loops.

What is the best way to use blockproc? What is wrong at my use of blockproc?

Thank you