matlab邊緣檢測演算法彙總2
阿新 • • 發佈:2019-01-23
4. 基於小波變換模極大值的邊緣檢測
具體實現步驟如下:
1 對於原始影象進行二進離散平穩小波變換;
2 通過變化係數,得到影象的水平方向和垂直方向的小波變換系數,並計算器小波變換的模值和梯度方向;
3 求區域性模極大值。
clear all; load wbarb; I = ind2gray(X,map);imshow(I); I1 = imadjust(I,stretchlim(I),[0,1]);figure;imshow(I1); [N,M] = size(I); h = [0.125,0.375,0.375,0.125]; g = [0.5,-0.5]; delta = [1,0,0]; J = 3; a(1:N,1:M,1,1:J+1) = 0; dx(1:N,1:M,1,1:J+1) = 0; dy(1:N,1:M,1,1:J+1) = 0; d(1:N,1:M,1,1:J+1) = 0; a(:,:,1,1) = conv2(h,h,I,'same'); dx(:,:,1,1) = conv2(delta,g,I,'same'); dy(:,:,1,1) = conv2(g,delta,I,'same'); x = dx(:,:,1,1); y = dy(:,:,1,1); d(:,:,1,1) = sqrt(x.^2+y.^2); I1 = imadjust(d(:,:,1,1),stretchlim(d(:,:,1,1)),[0 1]);figure;imshow(I1); lh = length(h); lg = length(g); for j = 1:J+1 lhj = 2^j*(lh-1)+1; lgj = 2^j*(lg-1)+1; hj(1:lhj)=0; gj(1:lgj)=0; for n = 1:lh hj(2^j*(n-1)+1)=h(n); end for n = 1:lg gj(2^j*(n-1)+1)=g(n); end a(:,:,1,j+1) = conv2(hj,hj,a(:,:,1,j),'same'); dx(:,:,1,j+1) = conv2(delta,gj,a(:,:,1,j),'same'); dy(:,:,1,j+1) = conv2(gj,delta,a(:,:,1,j),'same'); x = dx(:,:,1,j+1); y = dy(:,:,1,j+1); dj(:,:,1,j+1) = sqrt(x.^2+y.^2); I1 = imadjust(dj(:,:,1,j+1),stretchlim(dj(:,:,1,j+1)),[0 1]);figure;imshow(I1); end
5. 基於二維有限的特定角度邊緣檢測
數字濾波器根據其衝擊響應函式的時域特性可分為兩類:IIR(無限長衝擊響應濾波器)和FIR(有限長衝擊響應濾波器)。運用與有限衝擊響應卷積核相同的原理,可以檢測任意角度的邊緣。
有限衝擊響應卷積核:
% 輸入影象,並將其轉化成灰度影象
I=imread('qipan.jpg');
I=rgb2gray(I);
% 構造卷積核
F2=[-1 -1 0 0 -1
0 0 1 1 1];
% 進行卷積運算
A=conv2(double(I),double(F2));
% 轉換成8位無符號整型並顯示
A=uint8(A);
imshow(A)
檢測特定角度的邊緣:
% 輸入影象,並將其轉化成灰度影象 I=imread('qipan.jpg'); I=rgb2gray(I); f=im2double(I); choice = 0; % 構造卷積核 H = [-1 -1 -1;2 2 2;-1 -1 -1]; V = [-1 2 -1;-1 2 -1;-1 2 -1]; while(choice ~= 3) choice = input('1:Horizontal\n2:vertical\n3:Exit\nEnter your choice:'); %根據不同的要求與不同的卷積核進行濾波 switch choice case 1 DH = imfilter(f,H); figure(2),imshow(f),title('原始影象'); figure(3),imshow(DH),title('水平方向'); case 2 DV = imfilter(f,V); %figure(4),imshow(I),title('原始影象'); figure(5),imshow(DV),title('垂直方向'); case 3 display('Program Exited'); otherwise display('Wrong choice!!!'); end end
6. 基於多尺度形態學梯度的邊緣檢測
% 讀入並顯示原始影象
I=imread('**.jpg');
grayI=rgb2gray(I);
figure,imshow(grayI)
% 利用單尺度形態學梯度進行邊緣檢測
se=strel('square',3);
grad=imdilate(grayI,se)-imerode(grayI,se);
figure,imshow(grad)
% 利用多尺度形態學梯度進行邊緣檢測
se1=strel('square',1);
se2=strel('square',3);
se3=strel('square',5);
se4=strel('square',7);
grad1=imerode((imdilate(grayI,se2)-imerode(grayI,se2)),se1);
grad2=imerode((imdilate(grayI,se3)-imerode(grayI,se3)),se2);
grad3=imerode((imdilate(grayI,se4)-imerode(grayI,se4)),se3);
multiscaleGrad=(grad1+grad2+grad3)/3;
figure,imshow(multiscaleGrad)