Reconstruction from limited-angle projections based on δ - u spectrum analysis

Authors:
Jianhua Luo;Wanqing Li;Yuemin Zhu
Affiliations:
College of Life Science and Technology, Shanghai Jiao Tong University, Shanghai, China;School of Computer Science and Software Engineering, University of Wollongong, NSW, Australia;CREATIS, CNRS UMR, INSA Lyon, University of Lyon 1, Lyon, France
Venue:
IEEE Transactions on Image Processing
Year:
2010

Citing 3
Cited 1

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Limited Data X-Ray Tomography Using Nonlinear Evolution Equations

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Discrete tomography by convex-concave regularization and D.C. programming

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Image Reconstruction from Sparse Projections Using S-Transform

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Abstract

This paper proposes a sparse representation of an image using discrete δ -- u functions. A δ -- u function is defined as the product of a Kronecker delta function and a step function. Based on the sparse representation, we have developed a novel and effective method for reconstructing an image from limited-angle projections. The method first estimates the parameters of the sparse representation from the incomplete projection data, and then directly calculates the image to be reconstructed. Experiments have shown that the proposed method can effectively recover the missing data and reconstruct images more accurately than the total-variation (TV) regularized reconstruction method.