In sparse-angle X-ray
tomography reconstruction, where only a small number of projection images are
taken around the object, appropriate sinogram interpolation has a significant
impact on image quality. A
novel sinogram interpolation method is introduced for extreme sparse
tomographic reconstruction where only nine measured projection images are available.
The sinogram is interpolated by solving characteristics of the so-called warps, which can be considered as approximation sine waves in a limited
region. The numerical evidence suggests that this approach gives superior
results over standard interpolation methods when the tomographic data are extremely sparse and noisy.
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