Segmentation of video background regions based on a DTCNN-clustering approach

We propose a novel algorithm for segmentation of video background models in time-variant scenarios. It is robust to gradual or abrupt illumination changes, diverse kind of noises, and even scenario variation. The algorithm generates regions according to the scene composition by keeping region segmentation coherence. The proposed method based on a discrete-time cellular neural network estimates the number regions in the current background model, and then, a modified k-means algorithm is used to achieve segmentation. The findings demonstrate the robustness of the method and its superiority over two state of the art scene segmentation algorithms.     

A novel image fusion framework for night-vision navigation and surveillance

The night-vision image fusion plays a critical role in detecting targets and obstructions in low light or total darkness, which has great importance for pedestrian recognition, vehicle navigation, surveillance and monitoring applications. The central idea is to fuse low-light visible and infrared imagery into a single output. In this paper, we describe a new fusion framework for spatially registered visual and infrared images. The proposed framework utilizes the properties of fractal dimension and phase congruency in the non-subsampled contourlet transform (NSCT) domain. The proposed framework applies multiscale NSCT on visual and IR images to get low- and high-frequency bands. The varied frequency bands of the transformed images are then fused while exploiting their characteristics. Finally, the inverse NSCT is performed to get the fused image. The performance of the proposed framework is validated by extensive experiments on different scene imaginary, where the definite advantages are demonstrated subjectively and objectively.     

Color calibration of multi-view video plus depth for advanced 3D video

Multi-view video plus depth (MVD) format is considered as the next-generation standard for advanced 3D video systems. MVD consists of multiple color videos with a depth value associated with each texture pixel. Relying on this representation and by using depth-image-based rendering techniques, new viewpoints for multi-view video applications can be generated. However, since MVD is captured from different viewing angles with different cameras, significant illumination and color differences can be observed between views. These color mismatches degrade the performance of view rendering algorithms by introducing visible artifacts leading to a reduced view synthesis quality. To cope with this issue, we propose an effective method for correcting color inconsistencies in MVD. Firstly, to avoid occlusion problems and allow performing correction in the most accurate way, we consider only the overlapping region when calculating the color mapping function. These common regions are determined using a reliable feature matching technique. Also, to maintain the temporal coherence, correction is applied on a temporal sliding window. Experimental results show that the proposed method reduces the color difference between views and improves view rendering process providing high-quality results.     

Padé approximants for functions with branch points — strong asymptotics of Nuttall–Stahl polynomials

Let f be a germ of an analytic function at infinity that can be analytically continued along any path in the complex plane deprived of a finite set of points, \({f \in \mathcal{A}(\bar{\mathbb{C}} \setminus A)}\), \({\# A< \infty}\). J. Nuttall has put forward the important relation between the maximal domain of f where the function has a single-valued branch and the domain of convergence of the diagonal Padé approximants for f. The Padé approximants, which are rational functions and thus single-valued, approximate a holomorphic branch of f in the domain of their convergence. At the same time most of their poles tend to the boundary of the domain of convergence and the support of their limiting distribution models the system of cuts that makes the function f single-valued. Nuttall has conjectured (and proved for many important special cases) that this system of cuts has minimal logarithmic capacity among all other systems converting the function f to a single-valued branch. Thus the domain of convergence corresponds to the maximal (in the sense of minimal boundary) domain of single-valued holomorphy for the analytic function \({f\in\mathcal{A}(\bar{\mathbb{C}} \setminus A)}\). The complete proof of Nuttall’s conjecture (even in a more general setting where the set A has logarithmic capacity 0) was obtained by H. Stahl. In this work, we derive strong asymptotics for the denominators of the diagonal Padé approximants for this problem in a rather general setting. We assume that A is a finite set of branch points of f which have the algebro-logarithmic character and which are placed in a generic position. The last restriction means that we exclude from our consideration some degenerated “constellations” of the branch points.     

Simulation of oxidative stress of guanosine and 8-oxo-7,8-dihydroguanosine by electrochemically assisted injection–capillary electrophoresis–mass spectrometry

Oxidative stress plays a crucial role in DNA and RNA damage within biological cells. As a consequence, mutations of DNA can occur, leading to disorders like cancer and neurodegenerative and cardiovascular diseases. The oxidative attack of guanosine and 8-oxo-7,8-dihydroguanosine is simulated by electrochemistry coupled to capillary electrophoresis–mass spectrometry. The electrochemical conversion of the compound of interest is implemented in the injection protocol termed electrochemically assisted injection (EAI). In this way, oxidation products of guanosine can be generated electrochemically, separated by capillary electrophoresis, and detected by electrospray ionization time-of-flight mass spectrometry (EAI–CE–MS). A fully automated laboratory-made EAI cell with an integrated buffer reservoir and a compartment holding screen-printed electrodes is used for the injection. In this study, parameters like pH of the sample solution and the redox potential applied during the injection were investigated in terms of corresponding formation of well-known markers of DNA damage. The important product species, 8-oxo-7,8-dihydroguanosine, was investigated in a separate study to distinguish between primary and secondary oxidation products. A comparison of product species formed under alkaline, neutral, and acidic conditions is presented. To compare real biological systems with an analytical approach for simulation of oxidative stress, it is desirable to have a well-defined control over the redox potential and to use solutions, which are close to physiological conditions. In contrast to typical HPLC–MS protocols, the hyphenation of EAI, CE, and MS enables the generation and separation of species involved without the use of organic solvents. Thus, information of the electrochemical behavior of the nucleoside guanosine as well as the primary oxidation product 8-oxo-7,8-dihydroguanosine can be characterized under conditions close to the physiological situation. In addition, the migration behavior found in CE separations of product species can be used to identify compounds if several possible species have the same mass-to-charge values determined by MS detection.

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Weighted Information and Weighted Entropic Inequalities for Qutrit States

We review the notion of weighted quantum entropy and consider the weighted quantum entropy for bipartite and noncomposite quantum systems. We extend the subadditivity condition, the inequality known for the weighted entropy information, to the case of indivisible qudit system, such as a qutrit. We discuss the new inequality for the qutrit density matrix for different weights and states, as well as the role of weighted entropy with respect to nonlinear quantum channels.     

Adaptive registration of diffusion tensor images on lie groups

With diffusion tensor imaging (DTI), more exquisite information on tissue microstructure is provided for medical image processing. In this paper, we present a locally adaptive topology preserving method for DTI registration on Lie groups. The method aims to obtain more plausible diffeomorphisms for spatial transformations via accurate approximation for the local tangent space on the Lie group manifold. In order to capture an exact geometric structure of the Lie group, the local linear approximation is efficiently optimized by using the adaptive selection of the local neighborhood sizes on the given set of data points. Furthermore, numerical comparative experiments are conducted on both synthetic data and real DTI data to demonstrate that the proposed method yields a higher degree of topology preservation on a dense deformation tensor field while improving the registration accuracy.     

Sparse representation-based image restoration via nonlocal supervised coding

Sparse representation (SR) and nonlocal technique (NLT) have shown great potential in low-level image processing. However, due to the degradation of the observed image, SR and NLT may not be accurate enough to obtain a faithful restoration results when they are used independently. To improve the performance, in this paper, a nonlocal supervised coding strategy-based NLT for image restoration is proposed. The novel method has three main contributions. First, to exploit the useful nonlocal patches, a nonnegative sparse representation is introduced, whose coefficients can be utilized as the supervised weights among patches. Second, a novel objective function is proposed, which integrated the supervised weights learning and the nonlocal sparse coding to guarantee a more promising solution. Finally, to make the minimization tractable and convergence, a numerical scheme based on iterative shrinkage thresholding is developed to solve the above underdetermined inverse problem. The extensive experiments validate the effectiveness of the proposed method.     

Phase-I trigger readout electronics upgrade of the ATLAS liquid-argon calorimeters

This article gives an overview of the Phase-I Upgrade of the ATLAS LAr Calorimeter Trigger Readout. The design of custom developed hardware for fast real-time data processing and transfer are presented. Performance results from the prototype boards operated in the demonstrator system, first measurements of noise behavior and responses on the test pulses to the demonstrator system are shown.