Discrete Fourier transform (DFT) is one of the most wildly used tools for signal processing. In this paper, a novel sliding window algorithm is presented for fast computing 2D DFT when sliding window shifts more than one-point. The propose algorithm computing the DFT of the current window using that of the previous window. For fast computation, we take advantage of the recursive process of 2D SDFT and butterfly-based algorithm. So it can be directly applied to 2D signal processing. The theoretical analysis shows that the computational complexity is equal to 2D SDFT when one sample comes into current window. As well, the number of additions and multiplications of our proposed algorithm are less than those of 2D vector radix FFT when sliding window shifts mutiple-point.
KEYWORDS: Algorithm development, Medical imaging, Image quality, Digital signal processing, Multidimensional signal processing, Parallel processing, Image compression, Image processing, Current controlled current source, Computing systems
In this paper, we present a fast algorithm for computing the two-dimensional (2-D) discrete Hartley transform (DHT). By
using kernel transform and Taylor expansion, the 2-D DHT is approximated by a linear sum of 2-D geometric moments.
This enables us to use the fast algorithms developed for computing the 2-D moments to efficiently calculate the 2-D
DHT. The proposed method achieves a simple computational structure and is suitable to deal with any sequence lengths.
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