MATLAB: A null assignment can have only one non-colon index. When I eliminated elements of matrix

matrix

Finally I accept this command

 croppedImage = fullImage(row1:row2, col1:col2, :);

—

 [iH, iW]=size(I(:,:,1));  
 [iHo, iWo]=size(O(:,:,1));  %original image size
 if iH > iW  
       I(:,:,1:3)=[ I(:,:,1:3) zeros((iH-iW),iH,3)];
       iW=iH;
       Z=1;
 elseif iH<iW
       I(:,:,1:3)=[ I(:,:,1:3);zeros((iW-iH),iW,3)];
       iH=iW;
       Z=-1;
 else
       Z=0;
 end

1 Judge the shape of the image. If it is not square, make it square by adding black pixels.

2 After arnold and unarnold transforming, I want to remove the black pixels

if iHo>iWo
  outImg(iHo,(iHo-iWo),1:3)=[];
else if iHo<iWo
  outImg((iWo-iHo),iHo,1:3)=[];
  end
end
 figure
 imshow(outImg);

A null assignment can have only one non-colon index.

Error in unarnold (line 49)
  outImg(iHo,(iHo-iWo),1:3)=[];

Best Answer

You cannot do that. You have a color image. Now imagine that you have identified some pixel in the image, say the one at the top left (1,1). Now you want to remove that pixel. Well, you can't. You can't even do it with a 2-D image, much less a 3-D color image. Let's say you had a 2-D 2 by 2 image like this:

100 140
210 155

Now you want to remove the 100 and be left with an image like this:

      140
  210 155

Well, the image would no longer be rectangular as is required. You can't have an L-shaped image. You can set that pixel to zero or some other value, but you can't just get rid of it since images must remain rectangular.

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MATLAB: Straightening Image from RF data

Do you have a calibration from RF signal to kilograms, and from pixels to µm? And are you sure you really need to straighten the thing? Why isn't just going column by column enough? If you did, I'd probably start by thresholding and then going column by column to get the midpoint, like this code:

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
imtool close all;  % Close all imtool figures.
clear;  % Erase all existing variables.
workspace;  % Make sure the workspace panel is showing.
format longg;
format compact;
fontSize = 20;
% Read in a gray scale demo image.
folder = 'C:\Users\Srikanta\Documents';
baseFileName = 'tissue.png';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
% Check if file exists.
if ~exist(fullFileName, 'file')
  % File doesn't exist -- didn't find it there.  Check the search path for it.
  fullFileName = baseFileName; % No path this time.
  if ~exist(fullFileName, 'file')
    % Still didn't find it.  Alert user.
    errorMessage = sprintf('Error: %s does not exist in the search path folders.', fullFileName);
    uiwait(warndlg(errorMessage));
    return;
  end
end
grayImage = imread(fullFileName);
% Crop it.
grayImage = rgb2gray(imcrop(grayImage, [90 140 400 110]));
% Get the dimensions of the image.  
% numberOfColorBands should be = 1.
[rows columns numberOfColorBands] = size(grayImage);
% Display the original gray scale image.

subplot(2, 2, 1);
imshow(grayImage, []);
title('Original Grayscale Image', 'FontSize', fontSize);
% Enlarge figure to full screen.
set(gcf, 'units','normalized','outerposition',[0 0 1 1]);
% Give a name to the title bar.
set(gcf,'name','Demo by ImageAnalyst','numbertitle','off') 
% Let's compute and display the histogram.
[pixelCount grayLevels] = imhist(grayImage);
% Suppress the 0 bin:
pixelCount(1) = 0;
subplot(2, 2, 2); 
bar(pixelCount);
grid on;
title('Histogram of original image', 'FontSize', fontSize);
xlim([0 grayLevels(end)]); % Scale x axis manually.
% Get the binary image
binaryImage = grayImage > 10;
% Display the original gray scale image.
subplot(2, 2, 3);
imshow(binaryImage, []);
title('Binary Image', 'FontSize', fontSize);
% Smooth it out some and clean it up.
binaryImage = imclose(binaryImage, true(5));
binaryImage = imfill(binaryImage, 'holes')
subplot(2, 2, 4);
imshow(binaryImage, []);
title('Cleaned Binary Image', 'FontSize', fontSize);
% Get the midpoints
topRow = zeros(columns, 1);
bottomRow = zeros(columns, 1);
midpoints = zeros(columns, 1);
for column = 1 : columns
  oneColumn = binaryImage(:, column);
  if sum(oneColumn) > 0
    topRow(column) = find(binaryImage(:, column), 1, 'first');
    bottomRow(column) = find(binaryImage(:, column), 1, 'last');
    midpoints(column) = (topRow(column) + bottomRow(column)) / 2;
  end
end
hold on;
plot(1:columns, midpoints, 'r-', 'LineWidth', 2);

After that it gets tricky, though I've done it. You can go along the midpoint curve fitting a short stretch of it to a slowly varying curve and take perpendicular lines to get the profile. I posted code for that here just within the last two months or so.

MATLAB: How to simplify this command by avoiding cycle

bsxfun wouldn't work for this. sub2ind will, but it won't be pretty:

numpages = size(tempImg, 3);
destrows = repmat(ax(1:iH, 1:iW), 1, 1, numpages);
destcols = repmat(ay(1:iH, 1:iW), 1, 1, numpages);
destpages = repelem(permute(1:numpages, [1 3 2]), iH, iW);
[srcrows, srccols, srcpages] = ndgrid(1:iH, 1:iW, 1:numpages);
outImg(sub2ind(size(outImg), destrows, destcols, destpages)) = tempImg(sub2ind(size(tempImg), srcrows, srccols, srcpages));

Best Answer

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MATLAB: Straightening Image from RF data

MATLAB: How to simplify this command by avoiding cycle

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