FFT-Cost Implementation of HTH in Computed Tomography
Masih Nilchian, EPFL STI LIB
In order to formulate the reconstruction in computed tomography as an inverse problem, it is required to discretize the forward operator. One rigorous approach is projecting the object on a closed shift-invariant space V={f(x)=sum c_k s(x-k)} where s(x) is a generating function and taking advantage of linearity and pseudo shift-invariant property of the Radon transform to discretize the forward operator. Having a rigorous formulation introduces almost heavy computation cost. In this talk, we aim at addressing this issue. First, we present the necessary conditions on s(x) such that HTH be a filtering operator. Second, we consider how good this way of implementing works while using B-splines as basis functions.
Masih Nilchian, EPFL STI LIB
Seminar • 03 March 2014 • BM 4.233
AbstractIn order to formulate the reconstruction in computed tomography as an inverse problem, it is required to discretize the forward operator. One rigorous approach is projecting the object on a closed shift-invariant space V={f(x)=sum c_k s(x-k)} where s(x) is a generating function and taking advantage of linearity and pseudo shift-invariant property of the Radon transform to discretize the forward operator. Having a rigorous formulation introduces almost heavy computation cost. In this talk, we aim at addressing this issue. First, we present the necessary conditions on s(x) such that HTH be a filtering operator. Second, we consider how good this way of implementing works while using B-splines as basis functions.