Wavelet-based reconstruction for limited-angle X-ray tomography

The aim of X-ray tomography is to reconstruct an unknown physical body from a collection of projection images. When the projection images are only available from a limited angle of view, the reconstruction problem is a severely ill-posed inverse problem. Statistical inversion allows stable solution of the limited-angle tomography problem by complementing the measurement data by a priori information. In this work, the unknown attenuation distribution inside the body is represented as a wavelet expansion, and a Besov space prior distribution together with positivity constraint is used. The wavelet expansion is thresholded before reconstruction to reduce the dimension of the computational problem. Feasibility of the method is demonstrated by numerical examples using in vitro data from mammography and dental radiology.     

Thermoelectric Effect Spectroscopy and Photoluminescence of High-Resistivity CdTe:In

Thermoelectric effect spectroscopy and photoluminescence techniques were used to study the defect levels in samples from three crystals of CdTe:In grown by the vertical gradient freeze method. The main goal of the investigation was to study defects, which strongly trap charge carriers or act as recombination centers in order to eliminate them from the technological process. The main difference among detecting and non-detecting samples was the absence of electron traps with a very high capture cross-section and energy 0.6 eV to 0.7 eV, which act as lifetime killers even at low concentrations. Recently published ab initio calculations show a complex of Te antisite and Cd vacancy within this energy range.     

Efficient disparity vector prediction schemes with modified P frame for 2D camera arrays

An efficient disparity estimation algorithm for multi-view video sequences, recorded by a two-dimensional camera array in which the cameras are spaced equidistantly, is presented. Because of the strong geometrical relationship among views, the disparity vectors of a certain view can for most blocks be derived from the disparity vectors of other views. A frame constructed using that idea is called a D frame in this work. Three new prediction schemes which contain D frames are proposed for encoding 5 × 3 multi-view video sequences. The schemes are applied to several multi-view image sequences taken from a camera-array and they are compared in terms of quality, bit-rate and complexity. The experimental results show that the proposed prediction schemes significantly decrease the complexity of the encoder at a very low cost of quality and/or bit-rate.     

In vivo measurement of the brain and skull resistivities using an EIT-based method and realistic models for the head

In vivo measurements of equivalent resistivities of skull (rho(skull)) and brain (rho(brain)) are performed for six subjects using an electric impedance tomography (EIT)-based method and realistic models for the head. The classical boundary element method (BEM) formulation for EIT is very time consuming. However, the application of the Sherman-Morrison formula reduces the computation time by a factor of 5. Using an optimal point distribution in the BEM model to optimize its accuracy, decreasing systematic errors of numerical origin, is important because cost functions are shallow. Results demonstrate that rho(skull)/rho(brain) is more likely to be within 20 and 50 rather than equal to the commonly accepted value of 80. The variation in rho(brain)(average = 301 omega x cm, SD = 13%) and rho(skull)(average = 12230 omega x cm, SD = 18%) is decreased by half, when compared with the results using the sphere model, showing that the correction for geometry errors is essential to obtain realistic estimations. However, a factor of 2.4 may still exist between values of rho(skull)/rho(brain) corresponding to different subjects. Earlier results show the necessity of calibrating rho(brain) and rho(skull) by measuring them in vivo for each subject, in order to decrease errors associated with the electroencephalogram inverse problem. We show that the proposed method is suited to this goal.     

Self-Assembled Perovskite Nanoislands on CH3NH3PbI3 Cuboid Single Crystals by Energetic Surface Engineering

Organometal perovskite single crystals have been recognized as a promising platform for high-performance optoelectronic devices, featuring high crystallinity and stability. However, a high trap density and structural nonuniformity at the surface have been major barriers to the progress of single crystal-based optoelectronic devices. Here, the formation of a unique nanoisland structure is reported at the surface of the facet-controlled cuboid MAPbI₃ (MA = CH₃NH₃⁺) single crystals through a cation interdiffusion process enabled by energetically vaporized CsI. The interdiffusion of mobile ions between the bulk and the surface is triggered by thermally activated CsI vapor, which reconstructs the surface that is rich in MA and CsI with reduced dangling bonds. Simultaneously, an array of Cs-Pb-rich nanoislands is constructed on the surface of the MAPbI₃ single crystals. This newly reconstructed nanoisland surface enhances the light absorbance over 50% and increases the charge carrier mobility from 56 to 93 cm² V⁻¹ s⁻¹. As confirmed by Kelvin probe force microscopy, the nanoislands form a gradient band bending that prevents recombination of excess carriers, and thus, enhances lateral carrier transport properties. This unique engineering of the single crystal surface provides a pathway towards developing high-quality perovskite single-crystal surface for optoelectronic applications.     

Data-parallel intra decoding for block-based image and video coding on massively parallel architectures

With the increasing number of processor cores available in modern computing architectures, task or data parallelism is required to maximally exploit the available hardware and achieve optimal processing speed. Current state-of-the-art data-parallel processing methods for decoding image and video bitstreams are limited in parallelism by dependencies introduced by the coding tools and the number of synchronization points introduced by these dependencies, only allowing task or coarse-grain data parallelism. In particular, entropy decoding and data prediction are bottleneck coding tools for parallel image and video decoding. We propose a new data-parallel processing scheme for block-based intra sample and coefficient prediction that allows fine-grain parallelism and is suitable for integration in current and future state-of-the-art image and video codecs. Our prediction scheme enables maximum concurrency, independent of slice or tile configuration, while minimizing synchronization points. This paper describes our data-parallel processing scheme for one- and two-dimensional prediction and investigates its application to block-based image and video codecs using JPEG XR and H.264/AVC Intra as a starting point. We show how our scheme enables faster decoding than the state-of-the-art wavefront method with speedup factors of up to 21.5 and 7.9 for JPEG XR and H.264/AVC Intra coding tools respectively. Using the H.264/AVC Intra coding tool, we discuss the requirements of the algorithm and the impact on decoded image quality when these requirements are not met. Finally, we discuss the impact on coding rate in order to allow for optimal parallel intra decoding.     

TiN Nanoparticles for Enhanced THz Generation in TDS Systems

By virtue of the surface plasmon resonance effect, plasmonic nanoparticles (NPs) can localize the light field and significantly enhance the performance of some optoelectronic devices. In this work, NPs are employed for an enhanced generation of terahertz radiation from LT-GaAs-based antennas. Therefore, we have prepared plasmonic TiN NPs by direct ultrasonication (ULS) and pulsed laser ablation (PLA) techniques. The zeta potential, particle size, and absorbance were used to characterize the NPs in their colloidal forms in a comparison to commercial Au NPs. A layer of polydispersed titanium nitride (TiN) NPs prepared by PLA and deposited on the surface of an LT-GaAs device shows a significant improvement of terahertz signal generation from these devices with an enhancement of the peak to peak amplitude of 100%.     

Digital canvas removal in paintings

The periodic structure of the underlying support of paintings on canvas can become quite prominent and disturbing in high resolution digital recordings. In this paper, we construct a new model and method for the digital removal of canvas which is considered as a noise component superimposed on the painting artwork. The high resolution of the images prohibits the efficient application of existing adaptive denoising filters. Hence, a two-step approach is proposed. First a (smoothing) Wiener filter is applied to the complete image. The second step consists of a spatially adaptive extension with low-complexity to obtain a generic digital canvas removal filter.