What Kind of pre-processing techniques can I apply to make an object more clear?
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Hi,
I applied few techniques of denoising on MRI images and could not realize what techniques are applicable on my data to make the cartilage object more clear. First I applied Contrast-limited adaptive histogram equalization (CLAHE) with this function:
J = adapthisteq(I)
But I got a white image. This is original image and manual segmentation of two thin objects(cartilage):
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/163640/image.png)
And then I read a paper that they had used some preprocessing on microscopy images, such as: Anisotropic diffusion filter(ADF), then, K-SVD algorithm, and then Batch-Orthogonal Matching Pursuit (OMP). I applied the first two and the output is as following:
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/163642/image.png)
It seems my object is not clear. I do not what kind of algorithms are applicable to make the cartilage objects more clear. I really appreciate any help.
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Answers (1)
abbz123
on 6 Jun 2017
Edited: abbz123
on 6 Jun 2017
%Hi Sara, Try running the following commands on your image:
m = imread('mri.tif'); %Insert the name of your image within the ''
m2 = m + 50; %This adds 50 to every pixel in your image, making the entire image brighter
m2 = rgb2gray(m2); %Convert to grayscale so that we can filter the image appropriately
filt = fspecial('unsharp',0.5); %Unsharp filters sharpen image edges
mfiltered = filter2(filt,m2);
figure,imshow(m); figure,imshow(mfiltered)
%This will show the original image and your new & improved filtered image!
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