I have an algorithm that does a set of 8 image processing operations in an input image and then I want to show the output of each of them in a grid of 8 images. The problem is that I want to show image by image after each of the operations ends. By using subplot and imshow the image outputs I want to show in the grid are small.
Here is some piece of my code
output1=image_operation(input_image);
subplot(4,4,1);
imshow(output1);
I have heard about imdisp and montage functions, but they don't do what I want. I want to show the first image when the first algorithm ends, then the second image together with the first when the second algorithm ends and so on. What these functions do is showing all images at once and I don't want this.
Is there anything I missed?
The reason why your output images are too small is that you want to plot 8 images but you're using subplot command for 16 images i.e. subplot(4,4,x). Since you want to plot 8 images using subplot, use any of following instead:
subplot(4,2,x)
or subplot(2,4,x)
Related
I have roughly 160 images for an experiment. Some of the images, however, have clearly different levels of brightness and contrast compared to others. For instance, I have something like the two pictures below:
I would like to equalize the two pictures in terms of brightness and contrast (probably find some level in the middle and not equate one image to another - though this could be okay if that makes things easier). Would anyone have any suggestions as to how to go about this? I'm not really familiar with image analysis in Matlab so please bear with my follow-up questions should they arise. There is a question for Equalizing luminance, brightness and contrast for a set of images already on here but the code doesn't make much sense to me (due to my lack of experience working with images in Matlab).
Currently, I use Gimp to manipulate images but it's time consuming with 160 images and also just going with subjective eye judgment isn't very reliable. Thank you!
You can use histeq to perform histogram specification where the algorithm will try its best to make the target image match the distribution of intensities / histogram of a source image. This is also called histogram matching and you can read up about it on my previous answer.
In effect, the distribution of intensities between the two images should hopefully be the same. If you want to take advantage of this using histeq, you can specify an additional parameter that specifies the target histogram. Therefore, the input image would try and match itself to the target histogram. Something like this would work assuming you have the images stored in im1 and im2:
out = histeq(im1, imhist(im2));
However, imhistmatch is the more better version to use. It's almost the same way you'd call histeq except you don't have to manually compute the histogram. You just specify the actual image to match itself:
out = imhistmatch(im1, im2);
Here's a running example using your two images. Note that I'll opt to use imhistmatch instead. I read in the two images directly from StackOverflow, I perform a histogram matching so that the first image matches in intensity distribution with the second image and we show this result all in one window.
im1 = imread('http://i.stack.imgur.com/oaopV.png');
im2 = imread('http://i.stack.imgur.com/4fQPq.png');
out = imhistmatch(im1, im2);
figure;
subplot(1,3,1);
imshow(im1);
subplot(1,3,2);
imshow(im2);
subplot(1,3,3);
imshow(out);
This is what I get:
Note that the first image now more or less matches in distribution with the second image.
We can also flip it around and make the first image the source and we can try and match the second image to the first image. Just flip the two parameters with imhistmatch:
out = imhistmatch(im2, im1);
Repeating the above code to display the figure, I get this:
That looks a little more interesting. We can definitely see the shape of the second image's eyes, and some of the facial features are more pronounced.
As such, what you can finally do in the end is choose a good representative image that has the best brightness and contrast, then loop over each of the other images and call imhistmatch each time using this source image as the reference so that the other images will try and match their distribution of intensities to this source image. I can't really write code for this because I don't know how you are storing these images in MATLAB. If you share some of that code, I'd love to write more.
We have a pdf page which contains one or more figures which are two-dimensional plots of experimental results. The figures may or may not be embedded in text. Each plot has the x and y axis with their labels and unit measurements marked in the plot. Inside each figure are one or more plots, each with a different color.
How can we convert the plot into a table of corresponding x and y values (say for 100 points) ?
I have already tried WebPlotDigitizer but it works only when the input is a standalone picture of a plot.
What I think I'll have to do is extract the plots from the PDF and process it further. Now, I am not able to find a tool for doing that. I have attached a sample PDF from which the plots have to be extracted.
Note that the 2 plots in the last page of the PDF are images and can be extracted readily(I've found a couple of software for those).The other plots are not images and the software are not able to extract them.
Is there any open source software that can achieve that?
Plots in this PDF file you have provided are made with vector drawings, so the only way to extract them is to convert PDF into image (i.e. render pages). Try ImageMagick's convert command line, see this answer
As Photoshop is very well scriptable, it is actually possible to extract images from a PDF programmatically (as opposed to pages; see Photoshop JavaScript documentation).
Then you have the whole set of instruments to adjust the images, so that further processing (interpretation) is easier to accomplish.
I am relatively new to Matlab image processing stuff. I will be precise:
I have a .tif image which I would like to load into Matlab and subsequently extract an array of points (x,y) by simple mouse clicking. For Example:
I click three times => 3 xy coordinates => 2 dim array in workspace with three rows.
Any ideas?
Thanks.
You should look into imread for loading tif image from disk.
You will find imshow useful for displaying the image you read from disk.
Finally, you can use ginput to interactively mark locations on the displayed image.
I am having an issue reading a single image of a stacked tiff in using imread. The tiff is 128-by-126. It reads in just fine with ImageJ, but I try reading it into Matlab for some processing and it creates an odd streak in the center of the image. With the origin of the image in the top left, rows 63 and 64 are repeated as rows 65 and 66, and the last two rows of the image, 125 and 126 are cut off. I can tell this is happening by visual comparison of the image displayed in matlab to the image displayed in ImageJ.
If I take the same tiff stack, and save the first frame in ImageJ, I don't have this issue. Even when displaying the outputted matlab image using ImageJ, I see the same issue. However, I would like to automate the process to save images from several tiff stacks as single tiff files, which I can't do in ImageJ, so I turned to Matlab and ran into this issue. I have included my code below. I tried reading the tiff in two different ways and got the same error. It seems to be related to the tiff stack and how matlab reads in the tiffs. I am using Matlab R2012b.
I have included links below to the static ImageJ image I am seeing and the static matlab image I am seeing. I have also included a link for loading the stacked tiff file that is generating these issues for me.
Note: When I have ImageJ output each frame as an individual tiff and I open the first frame from that output in matlab using the same code below, the image is correctly displayed. The error only occurs when reading in the first frame from the image stack in Matlab.
StackOverflow doesn't support embedding TIFF files, but you can view and download them from these links:
Stacked Tiff File - Data I am working with
What the first frame should look like - ImageJ
What I am seeing when loading the first frame in MATLAB
Code Used to Generate the Image
fname='C:\FileLocation\pcd144_012.tif';
im1=imread(fname,1)
imagesc(im1);
axis image; colormap gray;
I tried reading in the image as a tiff object to see if it solved the problem and this didn't work either. The image has two strips, and the last two lines of the first strip are the same as the first two lines of the last strip, which is why the middle lines seem to be repeated. It seems matlab is indexing reading my image in wrong, likely because it is not a square image. Am I just doing something wrong, or does matlab have a bug with respect to reading in non-square tiffs? Any ideas or suggestions for improvement?
First of, I kinda agree with horchler, that is, there is something wrong in your header.
We can easily observe that the StripByteCounts (15872) does not match width*height (128*126). This could be the reason you see the repetition in row 63 - 64 and 65 - 66.
Since the RowPerStrip = 64 and StripOffsets = [8,15880] may indicate that you have a 128*124 graph, Matlab perhaps uses last two rows in the first 64 rows to pad the missing rows at the beginning of the rest of the rows. So the total row can be filled up to 126. Well, this is just my guess for how Matlab handles the disagreement between dimension and ByteCounts.
After all, to your question, imread indeed alters image in Matlab when reading TIFF without issuing any warning. Bad job in imread reading TIFF, Matlab.
After observing your TIFF frames in one of your links, the TIFF seems to actually have image data with dimension 128*126. So if you trust the dimension indicating in the header, you would probably use fread to read the frames in your TIFF instead of using shaky imfread.
fname='pcd144_012.tif';
tiffInfo = imfinfo(fname);
framIndex = 1;
tiffWidth = tiffInfo(framIndex).Width; % image width
tiffHeight = tiffInfo(framIndex).Height; % image height
tiffStartOffset = tiffInfo(framIndex).StripOffsets(1); % Image data offset start point
tiffEndOffset = tiffInfo(framIndex).StripOffsets(2); % Image data offset end point
fid = fopen(fname);
fseek(fid,tiffStartOffset,'bof');
im1 = fread(fid,tiffWidth*tiffHeight,'*uint16'); % We knew this from BitsPerSample
fclose(fid);
im1 = reshape(im1,tiffWidth,tiffHeight); % Reshape the image data array
figure
imagesc(im1);
colormap gray;
axis xy;
axis image;
Now, while this may solve the weird Matlab imread behavior, however, the above result still does not match the picture you showed in your second link. According to the picture in the second link, it has 300 frames but the one you attached in your first link only has 30 frames. Maybe we are all looking at the wrong picture?
Basically what I'm trying to do is overlay two images using predefined points on each image.
The images will be of two different sizes probably or scaled differently, don't know this for sure yet. But the images are of the same thing. So what I want to do is say this spot on image one is the same as this spot on image 2. And do this for multiple spots and then have matlab resize or transform to get all those points lined up so that the two images can be overlayed. The thing thats confusing me is having matlab automatically adjust the images so that they can "fit" together.
I have no idea where to start on this, and was just hoping to get a general idea of what i may be able to do.
Just incase someone else knows how to do this I'll throw in what else I need to do. After the two images are on top of each other, one images will be a region map the other a real image. What I need matlab to do is count the amount of dots from the real image in each region of the map.
Thanks for any help.
What you are trying to do is called image registration which is a very common image processing task. You wont need to write much code because matlab has built in functions for this. You use the cp2tform to create a transform from the first to second image and can then apply the transform to the first image using imtransform function. The code will look something like this assuming x,y coordinates of the control points are in an m by 2 matrix called points1 for image1 and points2 for image2.
tform= cp2tform(points1, points2 , 'similarity');
imtransform(image1, tform);