Stitching sub images to reconstruct full image

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I have subdivided an image into 4x4 tiles and produced a subimage and obtained a binary imaged. I add each of these binary images to a binary stack using a loop.
After the loop, how do I reconstruct/stitch the sub binary images back to the full image size, so I can create a binary image representing the while raw image so to use as a mask:
My binary sub images are expressed as :
BI(:,:,i) %where i is 1:16 as I'm using 4x4 tiles
This is my approach that isn't working:
%Now combine binary images so to create regions to act as mask on original
%image
size(BI) %Confirm there are 16 planes of images in the binarystack
Binary=[]; %Create empty Binary Image that will hold reconstructed sub images
ct=0; %counter
for jj=1:tiles
for ii=1:tiles
ii
jj
ct=ct+1
startingCols(jj)
startingRows(ii)
Binary(startingCols(ii):endingCols(ii), startingRows(jj):endingRows(jj))=BI(:,:,ct);
figure(2)
subplot(4,4,ct)
imshow(BI(:,:,ct),[0,1])
Binary=BI;
end
end

Accepted Answer

Mohammad Abouali
Mohammad Abouali on 14 Jan 2015
Edited: Mohammad Abouali on 14 Jan 2015
Again, why don't you use blockproc()? :D
what you are asking, i.e. stitching the sub images into one big one, can be done in a single command using blockproc() as follows:
Binary=blockproc( reshape(1:16,4,4)', [1,1], @(x) BI(:,:,x.data) );
where Binary contains all the sub images placed in the order you show in the figure. 16 sub images are not much but if there were more you can even do this in parallel as easily as:
Binary =blockproc( reshape(1:16,4,4)', [1,1], @(x) BI(:,:,x.data), 'UseParallel',true);
  5 Comments
Mohammad Abouali
Mohammad Abouali on 14 Jan 2015
Edited: Mohammad Abouali on 14 Jan 2015
If you are just thresholding using graythresh you can write your blockproc like this
Binary=blockproc(OrigImage,[25,25],@(x) (im2bw(x.data,graythresh(x.data(:)))) )
That would threshold your image using Otsu's method and it is not global, the threshold is decided on each 25x25 tile separately. You don't need to divide the image into tiles, you don't need to spend time stitching them back.
Another approach is to use the function that ImageAnalyst told you.

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More Answers (6)

Iain
Iain on 13 Jan 2015
depending how you've done it....
BInew = permute(BI,[1 3 2]);
BInew = reshape(BInew,16*size(BI,1),[]);
ought to work.
  9 Comments
Iain
Iain on 13 Jan 2015
You'd need to change the reshapes, not the permute. You've got 16 tiles though.... (4 x 4)
BInew = reshape(BI,[25 25 tileshigh tileswide]);
BInew = permute(BInew,[1 3 2 4]);
BInew = reshape(BInew, 25*tileshigh, [])

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Image Analyst
Image Analyst on 13 Jan 2015
Why bother saying this:
Binary(startingCols(ii):endingCols(ii), startingRows(jj):endingRows(jj))=BI(:,:,ct);
if you're just going to say this
Binary=BI;
three lines later? Not only that, but you switched rows and columns. The first index should be rows, not columns as you have it, and the second index should be columns, not rows as you have it.
  15 Comments
Image Analyst
Image Analyst on 14 Jan 2015
See attached blockproc demos. And don't forget to look at Mohammad's last comment under his answer.

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Jason
Jason on 13 Jan 2015
Why does this approach not work:
ct=0;
for ii=1:4
for jj=1:4
ct=ct+1
Binary(startingCols(jj):endingCols(jj), startingRows(ii):endingRows(ii))=BI(:,:,ct);
end
end
imshow(Binary,[0,1])
  2 Comments
Iain
Iain on 13 Jan 2015
That should work provided you calculate startingcols etc. correctly.
Image Analyst
Image Analyst on 13 Jan 2015
The first index should be rows, not columns as you have it, and the second index should be columns, not rows as you have it.

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Alessandro Masullo
Alessandro Masullo on 13 Jan 2015
What about using mat2cell and cell2mat? It should be much easier.
  1 Comment
Jason
Jason on 13 Jan 2015
Hi, I don't see how this can reconstruct a full image from the subimages

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Jason
Jason on 14 Jan 2015
I've managed to get a solution where I first have to crop the image to ensure there number of pixels corresponding to integer tiling: (100 in my case). its not ideal, but it seems a big struggle to get the non integer tiles as well.
  3 Comments
Jason
Jason on 14 Jan 2015
local thresholding worked a lot better than global!
Image Analyst
Image Analyst on 14 Jan 2015
OK but you don't need to split apart your image to do that. You can get a better local thresholding using adapthisteq() to flatten your image and then use a global threshold, or use blockproc like Mohammad suggested. adapthisteq is like splitting your image apart into tons of tiles that are only a pixel apart and will be much better and more accurate than splitting your image into 4 tiles and then computing the threshold for the whole tile. You should really look into these methods.

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KHOR  WEI KOK
KHOR WEI KOK on 2 Sep 2016
Hi, I would like to ask, how you manage to show the line segmentation and numbering on your image axes?

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