Edge Flow: A Framework of Boundary Detection and Image Segmentation
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Sampling of linear canonical transformed signals
Signal Processing
New sampling formulae related to linear canonical transform
Signal Processing
Sampling and discretization of the linear canonical transform
Signal Processing
Eigenfunctions of linear canonical transform
IEEE Transactions on Signal Processing
Uncertainty Principle for Real Signals in the Linear Canonical Transform Domains
IEEE Transactions on Signal Processing - Part I
Digital Computation of Linear Canonical Transforms
IEEE Transactions on Signal Processing
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In recent years there has been a renewed interest in finding fast algorithms to compute accurately the linear canonical transform (LCT) of a given function. This is driven by the large number of applications of the LCT in optics and signal processing. The well-known integral transforms: Fourier, fractional Fourier, bilateral Laplace and Fresnel transforms are special cases of the LCT. In this paper we obtain an O(NlogN) algorithm to compute the LCT by using a chirp-FFT-chirp transformation yielded by a convergent quadrature formula for the fractional Fourier transform. This formula gives a unitary discrete LCT in closed form. In the case of the fractional Fourier transform the algorithm computes this transform for arbitrary complex values inside the unitary circle and not only at the boundary. This chirp-FFT-chirp transform approximates the ordinary Fourier transform more precisely than just the FFT, since it comes from a convergent procedure for non-periodic functions.