Image Rotation in MATLAB - Examples without imrotate function – Part 2

To flip an image left to right without using ‘fliplr’

Grayscale:

 A = imread('cameraman.tif');

 LR = A(1:end,end:-1:1);

 figure, subplot(1,2,1);imshow(A);title('original');         

         subplot(1,2,2);imshow(LR);title('Flipped left to right');

RGB Image:

RGB = imread('peppers.png');

 LR  = RGB(1:end,end:-1:1,:);

 figure, subplot(1,2,1);imshow(RGB);title('original');         

         subplot(1,2,2);imshow(LR);title('Flipped left to right');

To flip an image upside down without using ‘flipud’

Gray Scale:

 A = imread('liftingbody.png');

 UD = A(end:-1:1,1:end);

 figure, subplot(1,2,1);imshow(A);title('original');         

         subplot(1,2,2);imshow(UD);title('Upside Down');

RGB Image:

 UD = RGB(end:-1:1,1:end,:);

 figure, subplot(1,2,1);imshow(RGB);title('original');         

         subplot(1,2,2);imshow(UD);title('Upside Down');

MATLAB code to rotate a gray scale Image:

A = imread('cameraman.tif');

%Specify the degree

deg = 35;

%Find the midpoint

if(deg > 155)

    midx = ceil((size(A,1))/2);

    midy = ceil((size(A,2))/2);

else

    midx = ceil((size(A,2))/2);

    midy = ceil((size(A,1))/2);

end

[y,x] = meshgrid(1:size(A,2), 1:size(A,1));

[t,r] = cart2pol(x-midx,y-midy);

t1 = radtodeg(t)+deg;

%Convert from degree to radians

t = degtorad(t1);

%Convert to Cartesian Co-ordinates

[x,y] = pol2cart(t,r);

%Add the mid points to the new co-ordinates

tempx = round(x+midx);

tempy = round(y+midy);

if ( min(tempx(:)) < 0 )

   

newx = max(tempx(:))+abs(min(tempx(:)))+1;

tempx = tempx+abs(min(tempx(:)))+1;

else

    newx = max(tempx(:));

end

if( min(tempy( : )) < 0 )

   

newy = max(tempy(:))+abs(min(tempy(:)))+1;

tempy = tempy+abs(min(tempy(:)))+1;

else

    newy = max(tempy(:));

end

tempy(tempy==0) = 1;

tempx(tempx==0) = 1;

C = uint8(zeros([newx newy]));

for i = 1:size(A,1)

    for j = 1:size(A,2)

        C(tempx(i,j),tempy(i,j)) = A(i,j);

       

    end

  

end

figure,imshow(C);

Output = C;

%FILL THE HOLES OR GAPS-NEAREST NEIGHBOR

for i = 2:size(C,1)-1

    for j = 2:size(C,2)-1

       

        temp = C(i-1:i+1,j-1:j+1);

        if(temp(5)==0&&sum(temp(:))~=0)

            pt = find(temp~=0);

           

            [~,pos] = sort(abs(pt-5));

            Output(i,j) = temp(pt(pos(1)));

          

        end

       

    end

end

figure,imshow(uint8(Output));

EXPLANATION:

This is a faster implementation of the older versionand also the gaps are filled with the nearest neighbor .

MATLAB code to rotate a RGB Image

A=imread('peppers.png');

%Specify the degree

deg=45;

%Find the midpoint

if(deg>155)

    midx = ceil((size(A,1))/2);

    midy = ceil((size(A,2))/2);

else

    midx = ceil((size(A,2))/2);

    midy = ceil((size(A,1))/2);

end

[y,x] = meshgrid(1:size(A,2), 1:size(A,1));

[t,r] = cart2pol(x-midx,y-midy);

t1 = radtodeg(t)+deg;

%Convert from degree to radians

t = degtorad(t1);

%Convert to Cartesian Co-ordinates

[x,y] = pol2cart(t,r);

tempx = round(x+midx);

tempy = round(y+midy);

if ( min(tempx ( : ) ) < 0 )

   

newx = max(tempx(:))+abs(min(tempx(:)))+1;

tempx = tempx+abs(min(tempx(:)))+1;

else

    newx = max(tempx(:));

end

if( min(tempy ( : ) ) < 0 )

   

newy = max(tempy(:)) + abs(min(tempy(:)))+1;

tempy = tempy + abs(min(tempy(:)))+1;

else

    newy = max(tempy(:));

end

tempy(tempy==0) = 1;

tempx(tempx==0) = 1;

C = uint8(zeros([newx newy 3]));

for i = 1:size(A,1)

    for j = 1:size(A,2)

        

        C( tempx(i,j),tempy(i,j) ,:) = A(i,j,:);

      

       

    end

  

end

figure,imshow(C);

Output=C;

%FILL THE HOLES OR GAPS - NEAREST NEIGHBOR

for i = 2:size(C,1)-1

    for j = 2:size(C,2)-1

       

        temp = C(i-1:i+1,j-1:j+1,:);

        if(temp(5)==0 && sum(temp(:))~=0)

           

             pt = find(temp(:,:,1)~=0);

            [~,pos] = sort(abs(pt-5));

           

            temp = C(i-1:i+1,j-1:j+1,1);

            Output(i,j,1) = temp(pt(pos(1)));

           

            temp = C(i-1:i+1,j-1:j+1,2);

            Output(i,j,2) = temp(pt(pos(1)));

           

            temp = C(i-1:i+1,j-1:j+1,3);

            Output(i,j,3) = temp(pt(pos(1)));

        end

       

    end

end

figure,imshow(uint8(Output));title([num2str(deg),'Degree']);

UPSAMPLING IN MATLAB

Upsampling is the process of inserting zeros in between the signal value in order to increase the size of the matrix.  We will discuss about upsampling in both spatial and time domain.

1.      Upsampling in Spatial Domain

1.1  Upsampling using MATLAB built-in function

1.2  Upsampling in 1D

1.3  Upsampling in 2D or image matrix

2.      Upsampling in Frequency Domain

2.1  Upsampling a 1D signal

2.2  Upsampling a image matrix

UPSAMPLING IN SPATIAL DOMAIN:

Given: 1-D array of size 1xN

Upsample by factor of 2:  

Output: 1-D array of size 1x(2*N)

Where N represents length of the array, n represents the index starting from 0,1,2…,N

%UPSAMPLING USING MATLAB BUILT-IN FUNCTION 'UPSAMPLE'

A = 1:25;

B = upsample(A,2);

EXPLANATION:

The above MATLAB function will insert zeros in between the samples.

To upsample an array by ratio 2, update the output array as follows:

1.      If index(n) of the output array is divisible by 2(ratio), then update the output array with the value of the input array with index n/2

2.      Otherwise, insert zero

STEPS TO PERFORM:

1.      Consider an array A of size 1xM

2.      Obtain the upsample Ratio N

3.      Pre-allocate an array B of size 1x(M*N)

4.      If the index is divisible by N then update the array B with value of A else zero

MATLAB CODE:

%UPSAMPLING IN SPATIAL DOMAIN

A = 1:10;

%UPSAMPLING WITH RATIO 2

B = zeros([1 size(A,2)*2]);

B(1:2:end)=A;

%UPSAMPLING WITH RATIO N

N=3;

B=zeros([1 size(A,2)*N]);

B(1:N:end)=A;

EXPLANATION:

Let A = [1 2 3 4 5]

Let us upsample try to upsample A with ratio 2

Pre-allocate output matrix B = [0 0 0 0 0 0 0 0 0 0]

Substitute the value of the matrix A in indices divisible by the ratio i.e. 2 of matrix B

B(1:2:end) = A

Now B(1,3,5,7,9) =[1 2 3 4 5]

Thus B = [1 0 2 0 3 0 4 0 5 0]

NOTE:

Definition of upsampling is usually given assuming the index starts from zero. But in case of MATLAB, the index starts with one that is why the odd positions are considered instead of even.

STEPS TO PERFORM TO UPSAMPLE A 2D MATRIX:

MATLAB CODE:

%IMAGE UPSAMPLING

A = imread('cameraman.tif');

M = 2;

N = 3;

B = zeros([size(A,1)*M size(A,2)*N]);

B(1:M:end,1:N:end) = A;

figure,imagesc(B);colormap(gray);

sz = M*N;

H = fspecial('average',[sz sz]);

C = conv2(B,H,'same');

figure,imagesc(C);colormap(gray);

EXPLANATION:

The above image is the pixel representation of the zero inserted image. In each row, two zeros are inserted between the pixels and in the each column; single zero is inserted between the pixels. In spatial domain, inserting zeros will be quite visible so it’s advisable to perform any low pass filtering or approximation like spatial averaging or applying Gaussian.

In the above example, spatial averaging is done. In order to understand how spatial averaging is done using convolution check the following link:

 http://angeljohnsy.blogspot.com/2015/11/convolution-in-matlab.html

UPSAMPLING IN FREQUENCY DOMAIN

UPSAMPLING IN FREQUENCY DOMAIN

1.      Upsampling in Spatial Domain

1.1  Upsampling using MATLAB built-in function

1.2  Upsampling in 1D

1.3  Upsampling in 2D or image matrix

2.      Upsampling in Frequency Domain

2.1  Upsampling a 1D signal

2.2  Upsampling a image matrix

In Frequency domain, upsampling means nothing but the padding of zeros at the end of high frequency components on both sides of the signal.

STEPS TO PERFORM:

1.      Read an image

2.      Obtain the ratio to upsample

3.      Perform Fast Fourier Transform

4.      Shift the Low frequency components to the centre and High frequency components outside.

5.      Add zeros on both the sides of the image

6.      Shift the High frequency components to the centre and Low frequency components to the exterior (Inverse of fftshift)

7.      Perform Inverse Fast Fourier Transform

8.      Display the Upsampled Image

MATLAB CODE:

%UPSAMPLING IN FREQUENCY DOMAIN

%1D UPSAMPLING

FS = 100;

t  = 0:(1/FS):1;

A = 10*sin(2*pi*5*t);

figure,plot(t,A);

 

%FOURIER DOMAIN

FT = fft(A);

fq =linspace(-1/FS,1/FS,101);

figure,plot(fq,abs(FT));title('Before FFTSHIFT');

FT_s = fftshift(FT);

figure,plot(fq,abs(FT_s));title('After FFTSHIFT');

pad_zero = padarray(FT_s,[0 50]);

fq =linspace(-1/FS,1/FS,201);

figure,plot(fq,abs(pad_zero));title('After PADDING WITH ZEROS');

%INVERSE FOURIER TRANSFORM

IFT = ifft(ifftshift(pad_zero));

%UPSAMPLED SIGNAL

t1 = linspace(0,1,201);

figure,plot(t1,(IFT*2),'r',t,A,'g');

EXPLANATION:

Amplitude of the input original signal is 10 and the frequency is 5.

Similarly, the amplitude of the upsampled signal is 10 and the frequency is 5. The number of samples used to plot the signal is increased in the later case.

IMAGE UPSAMPLING IN FOURIER DOMAIN

MATLAB CODE:

%READ AN INPUT IMAGE

A = imread('cameraman.tif');

%RATIO

RatioM = 3;

RatioN = 2;

%UPSAMPLING OVER EACH ROW

mnrow = round(size(A,2)*(RatioM-1)/2);

% 1D FFT ON EACH ROW

row_fft = fft(A,[],2);

%PAD WITH ZEROS ON BOTH SIDES OF EACH ROW

pad_row = padarray(fftshift(row_fft,2),[0 mnrow]);

 

Logarthmic scale

%UPSAMPLING OVER EACH COLUMN

mncol = round(size(A,1)*(RatioN-1)/2);

% 1D FFT ON EACH COLUMN

col_fft = fft(pad_row,[],1);

%PAD WITH ZEROS ON BOTH SIDES OF EACH COLUMN

pad_col = padarray(fftshift(col_fft,1),[mncol 0]);

 

Logarthmic scale

%PERFORM 1D IFFT ON EACH COLUMN

ifft_col = ifft(ifftshift(pad_col,1),[],1);

%PERFORM 1D IFFT ON EACH ROW

ifft_col_row = ifft(ifftshift(ifft_col,2),[],2);

%DISPLAY THE IMAGE AFTER UPSAMPLING

res = abs(ifft_col_row);

res = uint8(res*(numel(res)/numel(A)));

figure,imagesc(res);

SIMPLE VERSION :

A = imread('cameraman.tif');

%RATIO

RatioM = 3;

RatioN = 2;

mnrow = round(size(A,2)*(RatioM-1)/2);

mncol = round(size(A,1)*(RatioN-1)/2);

%FFT ON 2D MATRIX

FT = fftshift(fft2(A));

%PADDING WITH ZEROS

pad_rc = padarray(FT,[mncol mnrow]);

%INVERSE FOURIER TRANSFORM

IFT = ifft2(ifftshift(pad_rc));

Img = uint8(abs(IFT)*(numel(IFT)/numel(A)));

figure,imagesc(Img);

Also Check : UPSAMPLING IN SPATIAL DOMAIN: