Iterative methods for tomographic image reconstruction have the computational cost of each iteration dominated by the computation of the (back)projection operator, which take roughly O(N3) floating point operations (flops) for N × N pixels images. Furthermore, classical iterative algorithms may take too many iterations in order to achieve acceptable images, thereby making the use of these techn...

The performance of an iterative reconstruction algorithm for X-ray tomography is strongly determined by the features of the used forward and backprojector. For this reason, a large number of studies has focused on the to design of projectors with increasingly higher accuracy and speed. To what extent the accuracy of an iterative algorithm is affected by the mathematical affinity and the similar...

We have previously described how imaging systems and image reconstruction algorithms can be evaluated on the basis of how well binary-discrimination tasks can be performed by a machine algorithm that “views” the reconstructions [l, 21. The present work examines the performance of a family of algorithmic observers viewing tomographic images reconstructed using the Cambridge Maximum Entropy softw...

In this paper the two indirect conductivity distribution reconstruction algorithms in electrical tomography are presented. The first algorithm based on the previous resistivity reconstruction and the second one based on the usage of the inverse measured voltages. Efficiency of the presented algorithms is compared with the efficiency of the direct conductivity distribution reconstruction algorit...

The estimation of phase errors from digital-holography data is critical for applications such as imaging or wavefront sensing. Conventional techniques require multiple i.i.d. data and perform poorly in the presence of high noise or large phase errors. In this paper, we propose a method to estimate isoplanatic phase errors from a single data realization. We develop a model-based iterative recons...

Fresnel coherent diffractive imaging (FCDI) is a relatively recent addition to the suite of imaging tools available at third generation x-ray sources. It shares the strengths of other coherent diffractive techniques: resolution limits that are independent of focusing optics, single-plane measurement and high dose efficiency. The more challenging experimental geometry and detailed reconstruction...

Based on the recent mathematical findings on solving the linear inverse problems with sparsity constraints by Daubechiesx et al., here we adapt a simultaneous algebraic reconstruction technique (SART) for image reconstruction from a limited number of projections subject to a sparsity constraint in terms of an invertible compression transform. The algorithm is implemented with an exemplary Haar ...

In ground based infrared imaging a well-known technique to reduce the influence of thermal and background noise is chopping and nodding, where four different signals of the same object are recorded from which the object is reconstructed numerically. Since noise in the data can severely affect the reconstruction, regularization algorithms have to be implemented. In this paper we propose to combi...