“…cheaper) means to compute H s (θ, r), compared with the 2D Fourier transform. The complexity analysis for computing different fast Hankel transform algorithms, which are available in, 15,16 show that most of the fast Hankel transform algorithms can achieve a complexity of O(N s log 2 N s ), where N s denotes the number of data points in each dimension. Compared to this, the complexities of traditional 2D discrete Fourier transform (DFT) and 2D fast Fourier transform (FFT) are O(N 4 s ) and O(10N 2 s log 2 N s ), respectively.…”