I know MATLAB has a built in Radon function, but I am working on implementing the radon transform in order to perform filtered back projection. As I started, my idea was multiple nested for loops for the summations at different theta values, this became pretty complex. I am not looking for source code, just suggestions on an approach. Any ideas are welcome.
%%Edit%%Edit: Here is what I have come up with so far, it works fairly well to perform the radon transform and create a sinogram
%%%This function takes an image, theta max and theta step %%% %%%and returns a 2D matrix where each row is the projection%%% %%%of the original image at different angles %%% %%%by rotating the image and summing the pixels %%%
function [R] = RadonTransform(img, theta, thetaStep)
%%%This function takes an image, theta max and theta step %%%
%%%and returns a 2D matrix where each row is the projection%%%
%%%of the original image at different angles %%%
%%%by rotating the image and summing the pixels %%%
function [R] = RadonTransform(img, theta, thetaStep)
%Obtain the image size in the x-direction
[x,y] = size(img);
%Set a matrix R to hold the projection data
R = zeros((theta/thetaStep)+1,x);
%Set vector for the angles to take projections at
angles = 0:thetaStep:theta;
%Matrix to hold all the rotated images separately to prevent blurring
rotatedImage = zeros(x,y,length(angles));
%Loop to rotate image and add up values for the projections
for i = 1:(length(angles))
%rotate the image starting with theta = 0 degrees
rotatedImage(:,:,i) = imrotate(img,angles(i),'nearest', 'crop');
%Sum the columns of img to get projection data
%Each row of R contains a projection at a certain theta
R(i,:) = sum(rotatedImage(:,:,i),1);
end
%Convert the matrix to a gray scale image in the range 0 to 255
R = mat2gray(R);
figure
imshow(R)
title('My Sinogram')
end
end
