Paper Info
Title
Novel Tensor Transform-Based Method Of Image Reconstruction From Limited-Angle Projection Data
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 splitting-signals of the tensor transform of the discrete image f(x(i), y(j)) 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 degrees, 30 degrees) and down to [0 degrees, 20 degrees). The experimental results show that the proposed method reconstructs images more accurately than the known method of convex projections and filtered back projection.
Year
DOI
Venue
2014
10.1117/12.2038255
COMPUTATIONAL IMAGING XII
Keywords
Field
DocType
Tomographic Imaging, image reconstruction, tensor representation
Iterative reconstruction,Computer vision,Tomographic reconstruction,Tensor,Image plane,Fourier transform,Artificial intelligence,Discrete Fourier transform,Real image,Image restoration,Physics
Conference
Volume
ISSN
Citations 
9020
0277-786X
0
PageRank 
References 
Authors
0.34
5
2
Name
Order
Citations
PageRank
Artyom M. Grigoryan113427.30
Nan Du282.46