Paper
7 March 2014 Novel tensor transform-based method of image reconstruction from limited-angle projection data
Author Affiliations +
Proceedings Volume 9020, Computational Imaging XII; 90200F (2014) https://doi.org/10.1117/12.2038255
Event: IS&T/SPIE Electronic Imaging, 2014, San Francisco, California, United States
Abstract
The tensor representation is an effective way to reconstruct the image from a finite number of projections, especially, when projections are limited in a small range of angles. The image is considered in the image plane and reconstruction is in the Cartesian lattice. This paper introduces a new approach for calculating the splittingsignals of the tensor transform of the discrete image f(xi, yj ) from a fine number of ray-integrals of the real image f(x, y). The properties of the tensor transform allows for calculating a large part of the 2-D discrete Fourier transform in the Cartesian lattice and obtain high quality reconstructions, even when using a small range of projections, such as [0°, 30°) and down to [0°, 20°). The experimental results show that the proposed method reconstructs images more accurately than the known method of convex projections and filtered backprojection.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Artyom M. Grigoryan and Nan Du "Novel tensor transform-based method of image reconstruction from limited-angle projection data", Proc. SPIE 9020, Computational Imaging XII, 90200F (7 March 2014); https://doi.org/10.1117/12.2038255
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CITATIONS
Cited by 4 scholarly publications.
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KEYWORDS
Image restoration

Reconstruction algorithms

Fourier transforms

Data processing

Image quality

Interference (communication)

Signal to noise ratio

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