2D Convolution - Sobel Filter. What is wrong?

16 次查看(过去 30 天)
img = imread('Davis_Hall.jpg');
% 'Davis_Hall.jpg':color image
img =double(rgb2gray(img));
Gx = double([-1 0 1;-2 0 2;-1 0 1]);
Gx=rot90(Gx,2);
Gy = double([-1 -2 -1; 0 0 0; 1 2 1]);
Gy=rot90(Gy,2);
I= img;
[r,c]=size(I);
Fx = zeros(r,c);
Fy = zeros(r,c);
I = padarray(I,[1 1]);
for i=2:r-1
for j=2:c-1
Fx(i,j)=sum(sum(Gx.*I(i-1:i+1,j-1:j+1)));
Fy(i,j)=sum(sum(Gy.*I(i-1:i+1,j-1:j+1)));
end
end
img=uint8(img);
FMag=sqrt(Fx.^2+Fy.^2);
figure(1)
imshow(img);
title('Original Image');
figure(2)
imshow((abs(Fx))./max(max(Fx)));
title('Gradient in X direction');
figure(3)
imshow(abs(Fy)./max(max(Fy)));
title('Gradient in Y direction');
figure(4)
imshow(FMag./max(max(FMag)));
title('Gradient Magnitude');
% IT IS Not Allowed to use: imfilter, conv2, filter2, conv

回答(2 个)

David Wilson
David Wilson 2019-9-12
Here's my (old) code for a sobel filter:
img = imread('Davis_Hall.jpg');
% 'Davis_Hall.jpg':color image
X =double(rgb2gray(img));
%% Start
Bx = [-1,0,1;-2,0,2;-1,0,1]; % Sobel Gx kernel
By = Bx'; % gradient Gy
Yx = filter2(Bx,X); % convolve in 2d
Yy = filter2(By,X);
G = sqrt(Yy.^2 + Yx.^2); % Find magnitude
Gmin = min(min(G)); dx = max(max(G)) - Gmin; % find range
G = floor((G-Gmin)/dx*255); % normalise from 0 to 255
image(G); axis('image')
colormap gray
Gives the following: DavisH.png

Nisreen Sulayman
Nisreen Sulayman 2019-9-12
Here is my results:
untitled.jpg
  10 个评论
Nisreen Sulayman
Nisreen Sulayman 2019-9-13
编辑:Nisreen Sulayman 2019-9-13
Didn't work!!
Maybe there is something wrong related to the "greader"
We have a good results ... still didn't accept the answer!! (even with first code I have a good results!!)
OR THERE is that kind of silly bug which I couldn't spot.
Nisreen Sulayman
Nisreen Sulayman 2019-9-20
How to normalize a convolved image?
I have got these messages after running
%read the image
img = imread('Davis_Hall.jpg');
I =double(rgb2gray(img));
%Gx = double([-1 0 1;-2 0 2;-1 0 1]);
Gx=[-1 0 1;-2 0 2;-1 0 1];
Gx=rot90(Gx,2);
%Gy = double([-1 -2 -1; 0 0 0; 1 2 1]);
Gy=[-1 -2 -1; 0 0 0;1 2 1];
Gy=rot90(Gy,2);
[r,c]=size(I);
Fx = zeros(r,c);
Fy = zeros(r,c);
FMag=zeros(r,c);
I = padarray(I,[1 1],0,'both');
for i=2:r-1
for j=2:c-1
Fx(i,j)=sum(sum(Gx.*I(i-1:i+1,j-1:j+1)));
Fy(i,j)=sum(sum(Gy.*I(i-1:i+1,j-1:j+1)));
FMag(i,j)=sqrt(power(Fx(i,j),2)+power(Fy(i,j),2));
end
end
Fx=Fx(2:r-1,2:c-1);
Fy=Fy(2:r-1,2:c-1);
FMag=FMag(2:r-1,2:c-1);
img=uint8(img);
figure(1)
imshow(img);
title('Original Image');
figure(2)
imshow((abs(Fx))./max(max(Fx)));
title('Gradient in X direction');
figure(3)
imshow(abs(Fy)./max(max(Fy)));
title('Gradient in Y direction');
figure(4)
imshow(FMag./max(max(FMag)));
title('Gradient Magnitude');
%Fx may have negative values and values which are greater than 255, hence normalize before visualiz
%Fy may have negative values and values which are greater than 255, hence normalize before visualizin
%FMag may have values which are greater than 255, hence normalize before visualizing

请先登录,再进行评论。

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by