Electrical capacitance tomography (ECT) is used to obtain information about the distribution of a mixture of dielectric materials inside a vessel or pipe. ECT has several advantages over other reconstruction algorithms and has found many applications in the industrial fields. However, there are some difficulties with image reconstruction in ECT: The relationship between the permittivity distrib...

Abstract For future MeV-scale neutrino experiments, a Cherenkov scintillation detector, CSD, is of particular interest for its capability to reconstruct both energy and direction charged particles. A type new target material, slow liquid scintillator, SlowLS, which can be used separate lights, one the options detectors. multi-hundred ton spherical CSD simulated using Geant4-based Monte Carlo so...

In this paper, we present an iterative algorithm for reconstructing a three-dimensional density function from a set of two dimensional electron microscopy images. By minimizing an energy functional consisting of a fidelity term and a regularization term, an L(2)-gradient flow is derived. The flow is integrated by a finite element method in the spatial direction and an explicit Euler scheme in t...

In this paper, we propose an iterative reconstruction algorithm which uses available information from one dataset collected using one modality to increase the resolution and signal-to-noise ratio of one collected by another modality. The method operates on the structural information only which increases its suitability across various applications. Consequently, the main aim of this method is to...

The paper gives a practical rapid algorithm for doing projective reconstruction of a scene consisting of a set of lines seen in three or more images with uncalibrated cameras. The algorithm is evaluated on real and ideal data to determine its performance in the presence of varying degrees of noise. By carefully consideration of sources of error, it is possible to get accurate reconstruction wit...

Image super resolution reconstruction has important significance in remote sensing image feature extraction and classification etc.. Because the remote sensing image size is larger, it is difficult to super resolution reconstruction using multiple images, the compressed sensing (CS) theory was introduced into the super-resolution reconstruction. Algorithm designed the low pass filter to reduce ...

This letter considers the problem of sparse signal reconstruction from the timing of its Level Crossings (LC)s. We formulate the sparse Zero Crossing (ZC) reconstruction problem in terms of a single 1-bit Compressive Sensing (CS) model. We also extend the Smoothed L0 (SL0) sparse reconstruction algorithm to the 1-bit CS framework and propose the Binary SL0 (BSL0) algorithm for iterative reconst...