The Community for Technology Leaders
Green Image
<p>Efficient algorithms for the continuous representation of a discrete signal in terms of B-splines (direct B-spline transform) and for interpolative signal reconstruction (indirect B-spline transform) with an expansion factor m are described. Expressions for the z-transforms of the sampled B-spline functions are determined and a convolution property of these kernels is established. It is shown that both the direct and indirect spline transforms involve linear operators that are space invariant and are implemented efficiently by linear filtering. Fast computational algorithms based on the recursive implementations of these filters are proposed. A B-spline interpolator can also be characterized in terms of its transfer function and its global impulse response (cardinal spline of order n). The case of the cubic spline is treated in greater detail. The present approach is compared with previous methods that are reexamined from a critical point of view. It is concluded that B-spline interpolation correctly applied does not result in a loss of image resolution and that this type of interpolation can be performed in a very efficient manner.</p>
direct spline transforms; B-spline transforms; continuous image representation; interpolation; discrete signal; interpolative signal reconstruction; z-transforms; convolution property; indirect spline transforms; linear filtering; transfer function; global impulse response; cubic spline; computerised picture processing; interpolation; splines (mathematics); transfer functions; Z transforms

M. Unser, A. Aldroubi and M. Eden, "Fast B-spline Transforms for Continuous Image Representation and Interpolation," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 13, no. , pp. 277-285, 1991.
94 ms
(Ver 3.3 (11022016))