【圖像處理】圖像分割的工作原理和算法實現（matlab實現）

實驗目的

1、掌握p參數分割的工作原理和算法實現
2、掌握均勻性度量法分割的工作原理和算法實現

實驗圖片

鏈接：https://pan.baidu.com/s/1gSpYLw9Xz5OK_hSqSGeUwQ
提取碼：o4au

實驗內容

實現P-參數法的圖像分割的代碼

測試代碼如下：

Im=imread('yw2_g.jpg'); 
[Im2]=pParam0(Im,0.7974);
imshow(Im2);

實驗代碼：

function Im2 = pParam0(im,perct)
bestDelta = inf;
BestThrd = 0;
[m,n] = size(im);
for Thrd = 0:255
    ind1 = find(im<=Thrd);
    ind2 = find(im>Thrd);
    if(~isempty(ind1) && ~isempty(ind2))
        p1 = length(ind1)/(m*n);
        p2 = length(ind2)/(m*n);
        Delta = abs(p2-perct);
        if(Delta < bestDelta)
            BestThrd = Thrd;
            bestDelta = Delta;
        end
    end
end
Im2 = zeros(m,n);
Im2( find(im > BestThrd) ) =1;
Im2 = logical(Im2);

實驗結果：

實現均勻性度量法的圖像分割的代碼

測試代碼：

Im=imread('cameraman.tif'); 
[Im2,BestClThrd]=jyxdl(Im);
imshow(Im2);

實驗代碼：

function [Im2,BestClThrd] = jyxdl(Im)
BestCost = inf;
BestClThrd = 0;
[m,n] = size(Im);
for ClThrd = 0:255
    ind1 = find(Im<=ClThrd);
    ind2 = find(Im>ClThrd);
    if(~isempty(ind1) && ~isempty(ind2))
        mu1 = mean(Im(ind1));
        mu2 = mean(Im(ind2));
        sigma1_sq = sum((Im(ind1)-mu1).^2);
        sigma2_sq = sum((Im(ind2)-mu2).^2);
        p1 = length(ind1)/(m*n);
        p2 = length(ind2)/(m*n);
        Cost = p1*sigma1_sq + p2*sigma2_sq;
        if( Cost < BestCost )
            BestClThrd = ClThrd;
            BestCost = Cost;
        end
    end
end
Im2 = zeros(m,n);
Im2 ( find(Im > BestClThrd )) =1;
Im2 = logical(Im2);
end

實驗結果：

學如逆水行舟，不進則退