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【图像增强】基于Frangi滤波器实现血管图像增强附matlab代码
2022-07-02 01:09:00 【Matlab科研工作室】
1 简介
针对眼底视网膜图像对比度低,受病变区域边界干扰,很难正确提取血管细节的问题提出了一种基于Frangi滤波器的视网膜血管分割的方法,仿真结果表明上述方法对细小血管的提取表现出良好的效果,具备很强的实用价值.
2 部分代码
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; endif(sigma>0)% Make 1D Gaussian kernelx=-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 imageHx=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');endelseHx=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');endelseerror('imgaussian:input','unsupported input dimension');endend
3 仿真结果

4 参考文献
[1]袁盼, 陈以. 基于多尺度Frangi滤波器的视网膜血管分割[J]. 现代信息科技, 2020.
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