I looked thoroughly in internet to see how to stitch sub-images but none corresponds to my need. So I am in need of an explanation before I understand how the whole programming process might go.
I have taken images of a line with a camera at a fixed distance and varying the camera position along the line with steps of 5mm and taking always an image. I continue until I take the final image of the end of the line.
I have the images stored in Excel as files (35files). I have already converted the files (images) into an array of 2D matrices.
So my question now is:
How do I stitch the images from the first sub-image to the last sub-image in MATLAB to get the final exact image of the line? How do I treat the different sub-images? I do not understand just the basics of stitching! How does the dimensions of the line gets preserved on the final image?
Related
I am a new user on image processing via Matlab. My first aim is applying the article and comparing my results and authors' results.
The article can be found here: http://arxiv.org/ftp/arxiv/papers/1306/1306.0139.pdf
First problem, Image Quality: In Figure 7, masks are defined but I couldn't reach the mask data set, and I use the screenshot so image quality is low. In my view, it can effect the results. Is there any suggestions?
Second problem, Merging images: I want to apply mask 1 on the Lena. But I don't want to use paint =) On the other hand, is it possible merging the images and keeping the lena?
You need to create the mask array. The first step is probably to turn your captured image from Figure 7 into a black and white image:
Mask = im2bw(Figure7, 0.5);
Now the background (white) is all 1 and the black line (or text) is 0.
Let's make sure your image of Lena that you got from imread is actually grayscale:
LenaGray = rgb2gray(Lena);
Finally, apply your mask on Lena:
LenaAndMask = LenaGray.*Mask;
Of course, this last line won't work if Lena and Figure7 don't have the same size, but this should be an easy fix.
First of all, You have to know that this paper is published in archive. when papers published in archive it is always a good idea to know more about the author and/or the university that published the paper.
TRUST me on that: you do not need to waste your time on this paper.
I understand your demand: but it is not a good idea to do get the mask by doing print screen. The pixel values that can be achieved by using print screen may not be the same as the original values. The zoom may change the size. so you need to be sure that the sizes are the same.
you can do print screen. past the image.
crop the mask.
convert rgb to gray scale.
threshold the gray scale to get the binary.
if you saved the image as jpeg. distortions because of high frequency edges will change edge shape.
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.
I have a 16bit voxel data set from which I need to extract the integer values for each voxel. The data set can be downloaded from here, it is the 'Head Aneuyrism 16Bits' data set (You need to click on the blood vessels image to download the 16bit version). Its size is 512x512x512, but I don't know whether it is greyscale or color, nor if that matters. Looking at the image on the website I'd guess that it is color, but I am not sure whether the image should be taken literally.
A related question on SO is the following: How can I read in a RAW image in MATLAB?
and the following on mathworks: http://www.mathworks.com/matlabcentral/answers/63311-how-to-read-an-n-dimensioned-matrix-from-a-binary-file
Thanks to the information in the answers to these questions I managed to extract some information from the file with matlab as follows:
fileID=fopen('vertebra16.raw','r');
A=fread(fileID,512*512*512,'int16');
B=reshape(A,[512 512 512]);
I don't need to visualise the image, I only need to have the integer values for each voxel, but I am not sure whether I am reading the information in the correct way with my script.
The only way I found to try and check whether I have the correct voxel values is to visualise B using the following:
implay(B)
Now, with the code above, and then using implay(B) I get a black and white movie with a white disc in the center and black background and some black pixels moving in the disc (I tried to upload a frame of the movie, but it didn't work). Looking at the image on the website from which I downloaded the file, the movie frames I get seem quite different from that image, so I'd conclude that I do not have the correct voxel values.
Here are some questions related to my problem:
Do I need to know whether the image is in grey scale or color to read the voxel values correctly?
On the data set website there is only written that the data set is in 16bit format, so how do I know whether I am dealing with signed or unsigned integers?
In the SO question linked to above they use 'uint8=>uint8'. I could not find this in the matlab manual, so I wonder whether 'uint8=>uint8' is an obsolete matlab notation for 'uint8' or if it does something different. I suspect that it does something different since if I use 'int16=>int16' instead of 'int16' in my code above I get a completely black movie with implay.
It looks like you read the data correctly.
The problem when displaying it is the scale of the values. implay seems to assume the values to be in [0,1] and therefore clamps all values to be in that range, where are your data range is [0,3000].
Simply doing
B = B / max(B(:))
will rescale your data to [0,1] and looking at the data again with
implay(B)
shows you something much more sensible.
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?
As per my understanding,
1. .eps format images are vector images.
2. When we draw something in word (like a flowchart) that is stored
as a vector image.
I am almost sure about the first, not sure about the second. Please correct me if I am wrong.
Assuming this two things, when a latex file (where .eps images are inserted) or a word file (that contains vector images) is converted into pdf, do the images get converted into raster images?
Also, I think PDFBox/xpdf can only extract raster images from the pdf (as they are embedded as XObjects), not vector images. Is that understanding correct? This question in stackoverflow is related, but have not been answered yet.
Your point 1 is incorrect, eps files are PostScript programs, they may contain vector information, or text or image data, or all of the above.
point 2 In PDF there isn't a 'vector image', an image means a bitmap and therefore cannot be vector.
If you convert a PostScript program to a PDF file, then the result depends entirely on the conversion program you use. In general vectors will be retained as vectors, and text as text. However it is entirely possible that an application might render the entire PostScript program and insert the result as an image in the PDF.
So the answer to your first question ("do the images get converted into raster images") is 'maybe, but probably not'.
I'm afraid I have no idea about the capabilities of PDFBox/xpdf, but since collections of vectors may not be arranged as 'images' (they could be held as Form XObjects, or Patterns) in any atomic fashion, there isn't any obvious way to know when to stop extracting. And what format would you store the result in anyway ?