Create composite mask, and apply this mask to an image

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Shane Browne
Shane Browne 2020-11-29
评论： Tarunbir Gambhir 2020-12-4
Hi,
Scanning samples using NIR, processing the spectra in matlab.
I have an image, and I need to create a mask to remove the background.
I have been instructed to snip sections of the image, creating masks.
I then have to combine these masks (x3) into one composite and apply it to the overall image. Removing the background.
CL below is a crop of image I5.
CL=I5(131:149,36:43,:);
[xC,yC,zC]=size(CL);
figure,imshow(mean(CL,3),[])
I searched through a loop showing each slice of the hypercube. Slice for example 69 has contrast between the item and the background.
The threshold excludes the background.
%%CL snip one
figure,
subplot(1,2,1),imshow(CL(:,:,69)<0.26,[])
subplot(1,2,2),histogram(unfold(CL(:,:,69)),100)
CL_mask=CL(:,:,69)<0.26;
%% CL3 my second crop of the image
CL3=I5(125:150, 15:34,:);
[xC3,yC3,zC3]=size(CL3);
figure,imshow(mean(CL3,3),[])
CL_mask3=CL3(:,:,81)<0.1;
%% CL4 snip four
CL4=I5(153:168,25:41,:);
[xC4,yC4,zC4]=size(CL4);
figure,imshow(mean(CL4,3),[])
CL_mask4=CL4(:,:,65)<0.24;
Is there a way to combine the three masks? CL_mask4 + CLmask3 + CL_mask ?
I am a beginner level user, but I can provide more info if it helps.
Help would be hugely appreciated.
Shane

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采纳的回答

Tarunbir Gambhir
Tarunbir Gambhir 2020-12-2
A better approach would be to use a single mask for your entire image. Start with a matrix of same size as your image and update it at locations where the threshold condition suffices inside the cropped regions.
Something like this could be done:
% Assuming the dimensions of image to be Spacial x Spacial x Spectral
mask = zeros(size(I5,[1,2])); % Initialize mask with zero across spacial dimensions
%% CL
mask(131:149,36:43)=I5(131:149,36:43,69)<0.26;
%% CL3
mask(125:150,15:34)=I5(125:150,15:34,81)<0.1;
%% CL4
mask(153:168,25:41)=I5(153:168,25:41,65)<0.24;
Repeating the mask value across all spectral slices and then dot-multiplication with the original image should give you the masked image.
%% Applying the mask to I5
final_image = I5 .* repmat(mask,[1 1 size(I5,3)]);
  2 个评论
Shane Browne
Shane Browne 2020-12-3
Thank you very much for the help it is greatly appreciated.
The image size was defined as:
[x,y,z]=size(I5);
I previously had a loop to check if a mask worked on all slices of the hypercube.
CL_mask=CL(:,:,69)<0.26;
CL_masked=zeros(size(CL));
for i=1:z
CL_masked(:,:,i)=CL(:,:,i).*CL_mask;
end
%taking a look through the slices to check the mask worked ok
figure,
for i=1:z
imshow(CL_masked(:,:,i),[]),title(sprintf('%d',i))
pause (0.1)
end
Is it possible to run a loop like this checking each slice with the new mask?
Tarunbir Gambhir
Tarunbir Gambhir 2020-12-4
Yes. After getting the mask you could use a "for" loop in this way to check if the mask worked for every slice.

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