Poster:Continuous FVR of Irregularly Sampled Data Using Gaussian RBFs
نویسندگان
چکیده
We describe a Fourier Volume Rendering (FVR) algorithm for datasets that are irregularly sampled and require anisotropic (e.g., elliptical) kernels for reconstruction. We sample the continuous frequency spectrum of such datasets by computing the continuous Fourier transform of the spatial interpolation kernel which is a radially symmetric Gaussian basis function (RBF) that may be anisotropically scaled. While in the frequency domain, we can apply signal processing filters to the dataset before performing an inverse 2D Fourier transform to obtain the X-ray projection.
منابع مشابه
Continuous Fourier Volume Rendering of Irregularly Sampled Data Using Anisotropic RBFs
We describe a Fourier Volume Rendering (FVR) algorithm for datasets that are irregularly sampled and require anisotropic (e.g., elliptical) kernels for reconstruction. We sample the continuous frequency spectrum of such datasets by computing the continuous Fourier transform of the spatial interpolation kernel which is a radially symmetric basis function (RBF) that may be anisotropically scaled....
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