[image enhancement] vascular image enhancement based on frangi filter with matlab code

1 brief introduction

The contrast of retinal image is low , Disturbed by the boundary of the lesion area , It is difficult to extract the details of blood vessels correctly Frangi The method of retinal blood vessel segmentation based on filter , The simulation results show that the above method has a good effect on the extraction of small blood vessels , It has strong practical value .

2 Part of the code

function I=imgaussian(I,sigma,siz)% IMGAUSSIAN filters an 1D, 2D color/greyscale or 3D image with an % Gaussian filter. This function uses for filtering IMFILTER or if % compiled the fast  mex code imgaussian.c . Instead of using a % multidimensional gaussian kernel, it uses the fact that a Gaussian % filter can be separated in 1D gaussian kernels.%% J=IMGAUSSIAN(I,SIGMA,SIZE)%% inputs,%   I: The 1D, 2D greyscale/color, or 3D input image with %           data type Single or Double%   SIGMA: The sigma used for the Gaussian kernel%   SIZE: Kernel size (single value) (default: sigma*6)% % outputs,%   J: The gaussian filtered image%% note, compile the code with: mex imgaussian.c -v%% example,%   I = im2double(imread('peppers.png'));%   figure, imshow(imgaussian(I,10));% % Function is written by D.Kroon University of Twente (September 2009)​if(~exist('siz','var')), siz=sigma*6; end​if(sigma>0)    % Make 1D Gaussian kernel    x=-ceil(siz/2):ceil(siz/2);    H = exp(-(x.^2/(2*sigma^2)));    H = H/sum(H(:));​    % Filter each dimension with the 1D Gaussian kernels\    if(ndims(I)==1)        I=imfilter(I,H, 'same' ,'replicate');    elseif(ndims(I)==2)        Hx=reshape(H,[length(H) 1]);        Hy=reshape(H,[1 length(H)]);        I=imfilter(imfilter(I,Hx, 'same' ,'replicate'),Hy, 'same' ,'replicate');    elseif(ndims(I)==3)        if(size(I,3)<4) % Detect if 3D or color image            Hx=reshape(H,[length(H) 1]);            Hy=reshape(H,[1 length(H)]);            for k=1:size(I,3)                I(:,:,k)=imfilter(imfilter(I(:,:,k),Hx, 'same' ,'replicate'),Hy, 'same' ,'replicate');            end        else            Hx=reshape(H,[length(H) 1 1]);            Hy=reshape(H,[1 length(H) 1]);            Hz=reshape(H,[1 1 length(H)]);            I=imfilter(imfilter(imfilter(I,Hx, 'same' ,'replicate'),Hy, 'same' ,'replicate'),Hz, 'same' ,'replicate');        end    else        error('imgaussian:input','unsupported input dimension');    endend

3 Simulation results

4 reference

[1] Yuan pan , Chen Yi . Based on multi-scale Frangi Retinal blood vessel segmentation based on filter [J]. Modern information technology , 2020.​

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