remove the background of an object in image using matlab

Question

I have a image with noise. i want to remove all background variation from an image and want a plain image .My image is a retinal image and i want only the blood vessel and the retinal ring to remain how do i do it? 1 image is my original image and 2 image is how i want it to be.

this is my convoluted image with noise

Answer 1

There are multiple approaches for blood vessel extraction in retina images.

You can find a thorough overview of different approaches in Review of Blood Vessel Extraction Techniques and Algorithms. It covers prominent works of many approache.

As Martin mentioned, we have the Hessian-based Multiscale Vessel Enhancement Filtering by Frangi et al. which has been shown to work well for many vessel-like structures both in 2D and 3D. There is a Matlab implementation, FrangiFilter2D, that works on 2D vessel images. The overview fails to mention Frangi but cover other works that use Hessian-based methods. I would still recommend trying Frangi's vesselness approach since it is both powerful and simple.

Aside from the Hesisan-based methods, I would recommend looking into morphology-based methods since Matlab provides a good base for morphological operations. One such method is presented in An Automatic Hybrid Method for Retinal Blood Vessel Extraction. It uses a morphological approach with openings/closings together with the top-hat transform. It then complements the morphological approach with fuzzy clustering and some post processing. I haven't tried to reproduce their method, but the results look solid and the paper is freely available online.

Answer 2

This is not an easy task.

Detecting boundary of blood vessals - try edge( I, 'canny' ) and play with the threshold parameters to see what you can get.
A more advanced option is to use this method for detecting faint curves in noisy images.

Once you have reasonably good edges of the blood vessals you can do the segmentation using watershed / NCuts or boundary-sensitive version of meanshift.

Some pointers:
- the blood vessals seems to have relatively the same thickness, much like text strokes. Would you consider using Stroke Width Transform (SWT) to identify them? A mex implementation of SWT can be found here.
- If you have reasonably good boundaries, you can consider this approach for segmentation.

Good luck.

Answer 3

I think you'll be more served using a filter based on tubes. There is a filter available which is based on the work done by a man called Frangi, and the filter is often dubbed the Frangi filter. This can help you with identifying the vasculature in the retina. The filter is already written for Matlab and a public version is available here. If you would like to read about the underlying research search for: 'Multiscale vessel enhancement', by Frangi (1998). Another group who's done work in the same field are Sato et.al. Sorry for the lack of a link in the last one, I could only find payed sites for looking at the research paper on this computer.

Hope this helps

Answer 4

Here is what I will do. Basically traditional image arithmetic to extract background and them subtract it from input image. This will give you the desired result without background. Below are the steps:

1. Use a median filter with large kernel as the first step. This will estimate the background.
2. Divide the input image with the output of step 1 [You may have to shift the denominator a little (+1) ] to avoid divide by 0.
3. Do the quantization to 8 or n bit integer based on what bit the original image is.
4. The output of step 3 above is the background. Subtract it from original image, to get the desired result. This clips all the negative values as well.