I have data that change in size and want to display them in the same window. The command
void ImageResize( BasicImage im, Number num_dim, Number... )
seems like a potential fit, but the syntax is not clear at all.
Let's say I have 512x5 data set and now it needs to be 367x5.
The , Number...) indicates that this command takes a different number of parameters, all of them interpreted as number parameters. Commands which do this, usually use one of their other parameters to specify how many such parameters follow.
A typical example for this is also the SliceN command.
In this particular case, the command not only allows you to change the size of the dimensions in the image, but also the number of dimensions. It is a very useful command to f.e. change a 2D image into a 3D stack or the like.
The command ImageResize( BasicImage im, Number num_dim, Number... ) does several things:
It replaces im in-place, so the meta-data, display and window remains the same
It adjusts the dimension calibration when the dimension size is changed. Here, the assumption is, that the field-of-view before and
after the resize is the same. (The command can be used to easily scale
images as shown in the example below.)
All values of the image im are set to zero. ( If you need to keep the values, you need to act on an image clone!)
Example 1: Resizing image with bilinar interpolation
image before := GetFrontImage()
number sx, sy
before.GetSize(sx,sy)
number factor = 1.3
image after := before.ImageClone()
after.ImageResize( 2, factor*sx, factor*sy ) // Adjusts the empty container with meta-data
after = warp(before, icol/factor, irow/factor ) // interpolate data
after.ShowImage()
Example 2: Extend 2D image into 3D stack
number sx = 100
number sy = 100
image img := RealImage("2D",4,sx,sy)
img = iradius* Random()
img.ShowImage()
OKDialog("Now into a stack...")
number sz = 10
img.ImageResize(3,sx,sy,sz) // All values are zero now!
img = iradius * Random()
Related
Here is the code that i used to display the DICOM image, When i give the full display range it shows burred image like left, and when i increase the lower display range the image looks more clear.
[img, map] = dicomread('D:\Work 2017\Mercy\trial\trial4\Export0000\MG0001.dcm');
info = dicominfo('D:\Work 2017\Mercy\trial\trial4\Export0000\MG0001.dcm' );
mini = min(img(:));
maxi = max(img(:));
figure,
subplot(131), imshow(img, [mini maxi]); title('Full display range')
subplot(132), imshow(img, [maxi*0.7 maxi]); title('70% and above display range')
subplot(133), imshow(img, [maxi*0.8 maxi]); title('80% and above display range')
I want to always see an image something similar to right side image without giving the display range that I used in the above code
Typically a DICOM will have WindowCenter and WindowWidth tags that specify the recommended window/level settings. You can convert these to color limits in the following way
% Get the DICOM header which contains the WindowCenter and WindowWidth tags
dcm = dicominfo(filename);
% Compute the lower and upper ranges for display
lims = [dcm.WindowCenter - (dcm.WindowWidth / 2), ...
dcm.WindowCenter + (dcm.WindowWidth / 2)];
% Load in the actual image data
img = dicomread(dcm);
% Display with the limits computed above
imshow(img, lims);
Or more briefly
lims = dcm.WindowCenter + [-0.5 0.5] * dcm.WindowWidth;
If those values aren't acceptable, then it's likely best to provide a user-adjustable window/level (such as the contrast tool in imtool) as there is unlikely any way to reliably get "acceptable" contrast since it is subjective.
So I have the code to import a stack of images, but I am getting an error: Subscripted assignment dimension mismatch.
myPath = 'E:\folder name\'; %'
fileNames = dir(fullfile(myPath, '*.tif'));
width = 1400;
height = 1050;
nbImages = length(fileNames);
C=uint8(zeros(width, height, nbImages));
for i=1:length(fileNames)
C(:,:,i)=imread(cat(2,'E:\folder name\',fileNames(i).name));
i
end
I understand that the error is originating from the for loop, but I don't know of any other way to fill in an empty matrix with images.
Your images must not be all the same size. You can handle this by using explicit assignment for the first two dimensions. This will zero-pad any images which are smaller than the rest.
im = imread(...);
C(1:size(im, 1), 1:size(im, 2), i) = im;
Also, there is a good chance that your images have multiple color channels (the third dimension), so you'll likely want to concatenate along the fourth dimension rather than the third.
C(:,:,:,i) = imread(...)
Obviously it all depends what you want to do with the images, but in general, if you want a "stack" of images (or a "stack" of anything, really), then it sounds like you should be collecting them as a cell array instead.
Also, the correct way to create safe filenames is using the fullfile command
e.g.
C = cell(1, length(nbImages));
for i = 1 : length (fileNames)
C{i} = imread (fullfile ('E:','folder name', fileNames(i).name));
end
If you really want to concatenate to a 3D matrix from your cell array, assuming you have checked this is possible, you can do this very easily using comma-separated-list generator syntax:
My3DMatrix = cat(3, C{:});
I have a image.mat of about 4MB.
The size of some image file can also be 4MB.
Can the image.mat be transferred to image file?
I tried this, but that doesn't do the trick:
load image.mat %load Iw
imshow(mat2gray(Iw))
imwrite(Iw,'image.png');
IwNew = imread('image.png');
isequal(Iw,IwNew)
The result is 0; am I misunderstanding something?
The number in Iw are very important, so Iw can not be changed.
Actually my real problem is how to store float numbers into an image?
But MATLAB does not support Tiff 6.0, so I'll have to find some workaround.
I am doing a blind watermarking,and the decimal fraction of a number in Iw is important because it involve the information about another image.So the Iw can not be changed.
Actually,Mathematica can store floating floating-point data:
But my programs are all in MATLAB.
According to Matlab documentation:
"If A is a grayscale or RGB color image of data type double or single, then imwrite assumes that the dynamic range is [0,1] and automatically scales the data by 255 before writing it to the file as 8-bit values."
In other words: imwrite performs automatic conversion from double to uint8.
if you wish to keep the values of Iw unchanged, save it as a mat file and not as an image.
If you do want to save it as an image - there is going to be some loss of information. In this case, there are two things which need to be done:
Change the dynamic range of the matrix to [0,1]. (in your case, the range is between -0.0035 to 255.0035. Also, the matrix contain inf values).
If you want to get an equality, scale IwNew by 255, and convert it to uint8.
Code:
load image.mat %load Iw
%step 1, change the dynamic range of the image to [0,1].
%One way to do it is by using mat2gray on each channel separately.
Iw(:,:,1) = mat2gray(Iw(:,:,1));
Iw(:,:,2) = mat2gray(Iw(:,:,2));
Iw(:,:,3) = mat2gray(Iw(:,:,3));
%write the image to file
imwrite(Iw,'image.png');
%read the image
IwNew=imread('image.png');
%scale it, and convert to uint 8
Iw2 = uint8(Iw*255);
%check equality
isequal(Iw2,IwNew)
Result:
ans =
1
Alternatively, if you want to convert IwNew to double, perform the following:
%conversion to double
Iw2 = double(IwNew)/255;
Notice that in this case, the matrices won't be equal to one another,
Due to the loss of information which happened during the imwrite process (conversion from double to uint8).
Instead, they will be epsilon-close to one another, where epsilon = 0.0001.
In order to test this, write the following:
%equality check
sum(abs(Iw2(:)-Iw(:))>0.0001)
Result:
ans =
0
My MATLAB (R2010a) with the image processing toolbox is perfectly capable of storing double-valued pixel values, and retrieve them without loss of data.
Here's a shameless copy of this answer:
% Some random, data of type double
A = 7.6*rand(10);
% Construct TIFF image...
t = Tiff('test.tif', 'w');
% ...with these custom parameters...
tagstruct = struct(...
'ImageLength' , size(A,1),...
'ImageWidth' , size(A,2),...
'Compression' , Tiff.Compression.None,...
'SampleFormat' , Tiff.SampleFormat.IEEEFP,... % floating point
'Photometric' , Tiff.Photometric.MinIsBlack,...
'BitsPerSample' , 64,... % 8 bytes / double
'SamplesPerPixel' , 1,...
'PlanarConfiguration', Tiff.PlanarConfiguration.Chunky);
t.setTag(tagstruct);
% ...and write it to disk.
t.write(A);
t.close();
% Read the data actually written, and check if all
% information was indeed preserved:
B = imread('test.tif');
isequal(A,B)
Result:
ans =
1
Adjust in obvious ways if you have more than 1 channel (RGB).
I'm trying to combine the two images based on the information from the mask. I'm using the color information from the background image if the mask is 0 and color information from foreground image if the mask is 1. Because the mask and both
Images are of the same size, I would like to use logical indexing of matrices to achieve this.
My attempt:
mask = imread('mask.png');
foreground = imread('fg.jpg');
background = imread('bg.jpg');
[r,c,~]=size(mask);
A = zeros(size(mask));
for i=1:r
for j=1:c
if mask(i,j) == 0
A(i,j,:) = background(i,j,:);
end
if mask(i,j) > 0
A(i,j,:) = foreground(i,j,:);
end
end
end
imshow(A);
The result looks like a flickering blue image, but I don't want that. Please help.
You can do this a bit more concisely:
f = double(foreground).*double(mask);
b = double(background).*double(~mask);
blend = f+b;
imshow(blend, []);
Using logical indexing you could also do
foreground(logical(mask)) = 0;
background(logical(~mask)) = 0;
blend = foreground+background;
The ISNOT operator '~' inverts your matrix in the second line, so you cut out the area you would like for background.
NOTE: This works for black and white (one channel). For coloured images see rayryeng's solution.
There are two problems with your code. The first problem is that you are trying to assign colour pixels to the output image A, yet this image is only two-dimensional. You want an image with three channels, not two. In addition, the output image type you are specifying is wrong. By default, the output image A is of type double, yet you are copying values into it that aren't double... most likely unsigned 8-bit integer.
As such, cast the image to the same type as the input images. Assuming both input images are the same type, initialize your A so that:
A = zeros(size(foreground), class(foreground));
This correctly makes a colour image with the same type as any of the inputs, assuming that they're both the same type.
Now, your for loop is fine, but it's better if you do this in one shot with logical indexing. If you want to use logical indexing, create a new image that's initially blank like what you've done, but then make sure your mask has three channels to match the number of channels the other images have. After, you simply need to index into each image and set the right locations accordingly:
mask = imread('mask.png');
foreground = imread('fg.jpg');
background = imread('bg.jpg');
[r,c,d]=size(mask); %// Change
%// If your mask isn't three channels, make it so
%// Change
if d ~= 3
mask = cat(3, mask, mask, mask);
end
A = zeros(size(foreground), class(foreground)); %// Change
A(mask) = foreground(mask); %// Assign pixels to foreground
A(~mask) = background(~mask); %// Assign pixels to background
imshow(A);
% Clean up the BlackAndWhiteCheckerBoard.bmp by making it a true
% bi-color image where
% ColorOne >=128
% ColorTwo <128
% If the
% Input: ColorOne, ColorTwo, BlackAndWhiteCheckerBoard.bmp
% Output: CleanCheckerBoard, CleanCheckerBoard.bmp <-- not a typo!
Here is what the checkboard image looks like:
I'm really unsure what to do. Help would be much appreciated!
That can be done very easily with Boolean operations. First read in the image, then use Boolean operations to set your pixels accordingly. Following the steps of your question definition, and assuming that you set your working directory in MATLAB to be where you have placed the image, do the following:
ColorOne = ...; %// You define here
ColorTwo = ...; %// You define here
im = imread('BlackAndWhiteCheckerBoard.bmp'); %// Read in the image
CleanCheckerBoard = im; % // Copy input to output
%// Set colours according to spec
CleanCheckerBoard(im >= 128) = ColorOne;
CleanCheckerBoard(im < 128) = ColorTwo;
%// Save your image
imwrite(CleanCheckerBoard, 'CleanCheckerBoard.bmp');
The question is poorly worded, but my assumption is that any intensities that are >= 128, you wish to set to ColorOne and those intensities that are < 128 you set to ColorTwo. If I have interpreted this incorrectly, please leave me a comment and I will adjust my code accordingly.
The above code will read in your image, and you must specify what ColorOne and ColorTwo are. After, I make a copy of this image to the output variable that is part of the spec, and then I use Boolean operations to do what I just mentioned in the previous paragraph. After, I take this new image and save this to a file called CleanCheckerBoard.bmp as specified in the spec.