图像清晰化处理源码程序 - vb源码程序

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标题：图像清晰化处理源码程序
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所属分类: VB源码资源类型：文件大小: 37.49 KB 上传时间: 2016-01-25 19:59:29 下载次数: 8 资源积分：1分提供者: xiaopeng2 图像清晰化处理源码程序

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图像清晰化处理源码程序，程序员在编程的过程中可以参考学习使用，希望对IT程序员有用，此源码程序简单易懂、方便阅读，有很好的学习价值！

function [outputImage, number_of_nuclei] = nuclei_counter(sourceImage, threshold)

% This script accept an input nuclei image taken under microscope,

% then preprocess the image with tophat and bottomhat filter, enhance its

% contrast by multiplying gamma. Convert it to binary image with a histogram

% based threshold, count the number of connected components and detect edges

% of nucleus with LoG filter, then plot edges. Or calculate distance transform

% and detect seed points,use watershed algorithm for segmentation.

% flow chart:

% input image ---> tophat/bottomhat filter ---> image enhancement--->binarization by a histogram based threshold

% ---> calculate seed points ---> segmentation or plot edges of blobs ---> count connected components

% refrence:

% * Yousef Al-Kofahi, et al. Improved Automatic Detection and Segmentation of Cell Nuclei in Histopathology Images.

% IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 57, NO. 4, APRIL 2010

% * Jos B.T.M, et al, The Watershed Transform: Defnitions, Algorithms and Parallelization Strategies

% Fundamenta Informaticae 41 (2001) 187{228

% Input

% sourceImage: 8 bits grayscale image;

% threshold: threshold [0 1] for binarization.

% Output:

% outputImage: source image with overlayed contour

% number_of_nuclei: number of nucleis in image

% If you have any ideas or improvements about this method, welcome to contact me 'zhyh8341@gmail.com'.

% display original image

image = sourceImage;

figure;imshow(image);

title('input image');

total = numel(image);

% apply top hat and bottom hat filter

se = strel('disk',30);

tophat = imtophat(image,se);

bottomhat = imbothat(image,se);

filterImage = image + (tophat - bottomhat);

se = strel('disk',15);

tophat = imtophat(filterImage,se);

bottomhat = imbothat(filterImage,se);

filterImage = filterImage + (tophat - bottomhat);

% calculate histogram of filtered image

% estimate more than 78.5% area is background (pi/4 = .785)

[counts,x] = imhist(filterImage);

ssum = cumsum(counts);

bg = .215*total;

fg = .99*total;

low = find(ssum>bg, 1, 'first');

high = find(ssum>fg, 1, 'first');

adjustedImage = imadjust(filterImage, [low/255 high/255],[0 1],1.8);

% image binarization, threshold is choosen based on experience

if(nargin < 2)

matrix = reshape(adjustedImage,total,1);

matrix = sort(matrix);

threshold = graythresh(matrix(total*.5:end));

end

binarization = im2bw(adjustedImage,threshold);

% open image and then detect edge using laplacian of gaussian

se2 = strel('disk',5);

afterOpening = imopen(binarization,se2);

nsize = 5; sigma = 3;

h = fspecial('log',nsize,sigma);

afterLoG = uint8(imfilter(double(afterOpening)*255,h,'same').*(sigma^2));

se2 = strel('disk',5);

afterOpening = imopen(binarization,se2);

number_of_nuclei = bwconncomp(afterOpening);

% % you can either use watershed method to do segmentation

% D = -bwdist(~afterOpening);

% D(~afterOpening) = -Inf;

% L = watershed(D);

outputImage = sourceImage + afterLoG*5;

figure;imshow(outputImage);

title('output image');

文件列表（点击上边下载按钮，如果是垃圾文件请在下面评价差评或者投诉）:

图像清晰化处理源码程序/
图像清晰化处理源码程序/Nuclei_Counter/
图像清晰化处理源码程序/Nuclei_Counter/example.m
图像清晰化处理源码程序/Nuclei_Counter/img01.JPG
图像清晰化处理源码程序/Nuclei_Counter/nuclei_counter.m

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