Simultaneous computation of Discrete Radon transform quadrants for efficient implementation on real time systems

Discrete Radon transform is a technique that allows to detect lines in images. It is much lighter to compute than Radon transforms based on Fourier slice theorem that use FFT as basis computing block. Even then, it is not that prone to optimal fine grain parallelization due to the need of running 4 passes to mirrored and flipped versions of the input in order to compute the 4 quadrants comprising 45 degrees each that arises of the decomposition of discrete lines in slope-intercept form. A new method is proposed that can solve the 4 quadrants simultaneously allowing for a more efficient parallelization. In higher dimensions Radon transform needs even more 'runs' of the basic algorithm, v.g., in 3 dimensions instead of 4 quadrants there are 12 dodecants to be solved. The proposed method can be extended to alleviate also the problem in those higher dimensions achieving an even greater gain.