Discrete Tomography: Reconstruction under Periodicity Constraints
نویسندگان
چکیده
This paper studies the problem of reconstructing binary matrices that are only accessible through few evaluations of their discrete X-rays. Such question is prominently motivated by the demand in material science for developing a tool for the reconstruction of crystalline structures from their images obtained by high-resolution transmission electron microscopy. Various approaches have been suggested for solving the general problem of reconstructing binary matrices that are given by their discrete X-rays in a number of directions, but more work have to be done to handle the ill-posedness of the problem. We can tackle this ill-posedness by limiting the set of possible solutions, by using appropriate a priori information, to only those which are reasonably typical of the class of matrices which contains the unknown matrix that we wish to reconstruct. Mathematically, this information is modelled in terms of a class of binary matrices to which the solution must belong. Several papers study the problem on classes of binary matrices on which some connectivity and convexity constraints are imposed. We study the reconstruction problem on some new classes consisting of binary matrices with periodicity properties, and we propose a polynomialtime algorithm for reconstructing these binary matrices from their orthogonal discrete X-rays. keywords: combinatorial problem, discrete tomography, binary matrix, polyomino, periodic constraint, discrete X-rays.
منابع مشابه
Algorithm for Reconstructing 3D-Binary Matrix with Periodicity Constraints from Two Projections
We study the problem of reconstructing a three dimensional binary matrices whose interiors are only accessible through few projections. Such question is prominently motivated by the demand in material science for developing tool for reconstruction of crystalline structures from their images obtained by high-resolution transmission electron microscopy. Various approaches have been suggested to r...
متن کاملA Convex Programming Algorithm for Noisy Discrete Tomography
A convex programming approach to discrete tomographic image reconstruction in noisy environments is proposed. Conventional constraints are mixed with noise-based constraints on the sinogram and a binarity-promoting total variation constraint. The noise-based constraints are modeled as confidence regions that are constructed under a Poisson noise assumption. A convex objective is then minimized ...
متن کاملDISCRETE TOMOGRAPHY AND FUZZY INTEGER PROGRAMMING
We study the problem of reconstructing binary images from four projections data in a fuzzy environment. Given the uncertainly projections,w e want to find a binary image that respects as best as possible these projections. We provide an iterative algorithm based on fuzzy integer programming and linear membership functions.
متن کاملReconstructing Binary Matrices under Window Constraints from their Row and Column Sums
The present paper deals with the discrete inverse problem of reconstructing binary matrices from their row and column sums under additional constraints on the number and pattern of entries in specified minors. While the classical consistency and reconstruction problems for two directions in discrete tomography can be solved in polynomial time, it turns out that these window constraints cause va...
متن کاملBi-Level 3D-Image Reconstruction from Two Orthogonal Projections with Periodicity and Sub
As the Computed Tomography (CT) requires normally hundreds of projections to reconstruct the image, patients are exposed to more X-ray energy, which may cause side effects such as cancer. Even when the variability of the particles in the object is very less, the Computed Tomography requires many projections for good quality reconstruction. Discrete Tomography makes use of less variability of th...
متن کامل