CODEWITHSUNDEEP
matlabimage-processingnearest-neighborimage-rotation
MeadowMuffins
MeadowMuffins

Reputation: 527

How To Rotate Image By Nearest Neighbor Interpolation Using Matlab

My Plain Code without interpolation: 

im1 = imread('lena.jpg');imshow(im1);    
[m,n,p]=size(im1);
thet = rand(1);
m1=m*cos(thet)+n*sin(thet);
n1=m*sin(thet)+n*cos(thet);    

for i=1:m
    for j=1:n
       t = uint16((i-m/2)*cos(thet)-(j-n/2)*sin(thet)+m1/2);
       s = uint16((i-m/2)*sin(thet)+(j-n/2)*cos(thet)+n1/2);
       if t~=0 && s~=0           
        im2(t,s,:)=im1(i,j,:);
       end
    end
end
figure;
imshow(im2);

This code creates black spot, the problem is how to do interpolation? Thank you all for any illumination. P.S. Not asking for build-in function: imrotate(im1,1/thet,'nearest');

Upvotes: 12

Views: 17701

Answers (4)

Fatima Zohra
Fatima Zohra

Reputation: 2967

Black Spots can be removed by these lines, while the rest of the code remains same:

im2= zeros(500,500);
im2(:)=1;

Upvotes: 0

sjchoi
sjchoi

Reputation: 628

To rotate the image without the black spots, you need to go in the reverse direction.

The inverse of the rotation matrix is the transpose of it. Also, the rotated image is always bigger with maximum being 45 degree rotation. Hence, the sqrt(2) factor

im1 = imread('lena.jpg');imshow(im1);  
[m,n,p]=size(im1);
thet = rand(1);
mm = m*sqrt(2);
nn = n*sqrt(2);
for t=1:mm
   for s=1:nn
      i = uint16((t-mm/2)*cos(thet)+(s-nn/2)*sin(thet)+m/2);
      j = uint16(-(t-mm/2)*sin(thet)+(s-nn/2)*cos(thet)+n/2);
      if i>0 && j>0 && i<=m && j<=n           
         im2(t,s,:)=im1(i,j,:);
      end
   end
end
figure;
imshow(im2);

Upvotes: 11

Jacob
Jacob

Reputation: 34621

Once you have all the transformed pixels, you can fill in the black spots with griddata which takes in a non-uniform spatial distribution of pixels (your rotated pixels) and interpolates the required pixels (your black spots) using linear, cubic or nearest-neighbor.

Upvotes: 0

Amro
Amro

Reputation: 124563

I remember a previous question on SO that had a similar problem.

The idea I had was to map the pixels in the opposite direction; for each pixel in the rotated image, find the pixel(s) that maps to it in the original image, then the problem becomes much simpler.

I don't have access to MATLAB at this moment, but I think it is doable. The difficulty here is looping over the rotated image pixels..

Upvotes: 6

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