A new approach for processing images based on joint application of the residue number system and finite-field wavelets is proposed in this work. It is shown that the residue number system with simple modules can be used for implementation of the digital processing of signals using finite-field wavelets. The principle of organization of computations in the wavelet transform of images in the residue number system is proposed. There are given examples showing how this method can be used for compression of images and protection of confidential information.

Digital filtering of images in a residue number system using finite-field wavelets

The multiframe image super-resolution (SR) has appeal great care due to its relevant practical applications. Since the SR methods are always considered as ill-posed problems, great interest is therefore investigated to reconstruct an image with less artefacts. In this paper, we propose a high-order partial differential equation (PDE) that preserve singularities and edge continuities while smoothing. This PDE is based on anisotropic diffusion behavior by adding some constraints to the Weickert coherence enhancing diffusion tensor in order to control the diffusion process near edges and avoids tiny corners destruction. In fact, this PDE combine between the diffusion process of Perona–Malik in the flat regions and the anisotropic diffusion of the Weickert model near strong edges. Moreover, the introduction of the high-order derivatives reduces unwanted artifacts such as staircasing. The given experimental results show the effectiveness of the proposed PDE compared to some competitive methods in both visually and quantitatively.

An edge preserving high-order PDE for multiframe image super-resolution

Micro-electro-mechanical systems (MEMS)-based cross-connects are widely used for all-optical switching in recent optical networks. This paper provides a brief overview of various photonic switching technologies and a detailed review of the working principles, actuating mechanisms, and architectures of MEMS-based optical cross-connects (OXCs) from the last two decades. New approaches, which, potentially, will be adopted in the next generation of MEMS-based cross-connects are also described. The switching MEMS-based cross-connects speed can vary from less than 1 ${\mu }\text{s}$ to tens of ms depending on the chosen switching mechanism and actuator parameters. This paper describes the various types of actuators used to manipulate the optical signal inside all-OXCs. Optical properties (insertion loss, crosstalk), switching speed, and scalability are also discussed.

A Comparative Review of MEMS-Based Optical Cross-Connects for All-Optical Networks From the Past to the Present Day

All-optical switching networks have been considered a promising candidate for the next generation data center networks thanks to its scalability in data bandwidth and power efficiency. However, the bufferless nature and the nonzero reconfiguration delay of optical switches remain great challenges in deploying all-optical networks. This paper considers the end-to-end scheduling for all-optical data center networks with no in-network buffer and nonzero reconfiguration delay. A framework is proposed to deal with the nonzero reconfiguration delay. The proposed approach constructs an adaptive variant of any given scheduling policy. It is shown that if a scheduling policy guarantees its schedules to have schedule weights close to the MaxWeight schedule (and thus is throughput optimal in the zero reconfiguration regime), then the throughput optimality is inherited by its adaptive variant (in any nonzero reconfiguration delay regime). As a corollary, a class of adaptive variants of the well-known MaxWeight policy is shown to achieve throughput optimality without prior knowledge of the traffic load. Furthermore, through numerical simulations, the simplest such policy, namely, the Adaptive MaxWeight, is shown to exhibit better delay performance than all prior work.

Adaptive Policies for Scheduling With Reconfiguration Delay: An End-to-End Solution for All-Optical Data Centers

Development and improvement of a mathematical model for a large-scale analysis based on the Daubechies discrete wavelet transform will be implemented in an algebraic system possessing a property of ring and field suitable for speech signals processing. Modular codes are widely used in many areas of modern information technologies. The use of these non-positional codes can provide high-speed data processing. Therefore, these algebraic systems should be used in the algorithms of digital processing of signals, which are characterized by processing large amounts of data in real time. In addition, modular codes make it possible to implement large-scale signal processing using the wavelet transform. The paper discusses examples of the Daubechies wavelet transform application. Integer processing, presented in the paper, will reduce the number of rounding errors when processing the speech signals.

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An Algorithm of Daubechies Wavelet Transform in the Final Field When Processing Speech Signals

Because of the feasible and impressive fallout, the classical Super-Resolution Reconstruction (SRR) is the contemporary algorithm for improving spatial information and reducing noise and SISR (Single-Image Super-Resolution) method, which is form on the classical SRR, is solely developed for improving spatial information. Disastrously, deficiency of the classical SISR method is conceptually computed from three specifications (b, h, k) and the simulating calculation of the optimized specifications for interpolating the better and higher spatial information images with highest PSNR is so burdersome. For figuring out this issue, the Geman&Mcclure function is proposed to replace with the ordinary SISR function because this function is conceptually computed from only one specification (T), contrary to three specifications similar to classical SISR method hence this analytic article focuses to offer a novel elementary spatial expanding scheme form on SISR method with modifying Geman&Mcclure function. Therefore, the fallout of a proposed spatial expanding scheme approximately matches to classical SISR method. From these reason, a novel elementary spatial expanding scheme is easily implemented for real works.

A novel elementary spatial expanding scheme form on SISR method with modifying geman & mcclure function

Since 1998, the Bilateral filter (BF) is worldwide accepted for its performance in practical point of view under Gaussian noise however the Bilateral filter has a poor performance for impulsive noise. Based on the combining of the Rank-Ordered Absolute Differences (ROAD) detection technique and the Bilateral filter for automatically reducing or persecuting of impulsive and Gaussian noise, this Trilateral filter (TF) has been proposed by Roman Garnett et al. since 2005 but the Trilateral filter efficiency is rest absolutely on spatial, radiometric, ROAD and joint impulsivity variance. Hence, this paper computationally determines the optimized values of the spatial, radiometric, ROAD and joint impulsivity variance of the Trilateral filter (TF) for maximum performance. In the experiment, nine noisy standard images (Girl-Tiffany, Pepper, Baboon, House, Resolution, Lena, Airplain, Mobile and Pentagon) under both five power-level Gaussian noise setting and five density impulsive noise setting, are used for estimating optimized parameters of Trilateral filter and for demonstrating the its overall performance, which is compared with classical noise removal techniques such as median filter, linear smoothing filter and Bilateral filter (BF). From the noise removal results of empirically experiments with the highest PSNR criterion, the trilateral filter with the optimized parameters has the superior performance because the ROAD variance and joint impulsivity variance can be statistically analyzed and estimated for each experimental case.

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An Empirical Evaluation of the Parameters of Trilateral Filter for Noise Removal Implementation on Gaussian and Impulsive Noise

Nowadays, many protocols have been designed to support smart grid system due to the massively of transferred data, reliability and the constrained of environment. RPL protocols have been designed to support with these constrains of networks: energy, memory, power and interconnection. To improve the performance, ETX and energy balance metrics must be use in RPL networks. In this paper, we propose Weight Ranking Mechanism of energy balancing routing metric algorithm which can prolong a better life-time as compared to the conventional RPL routing metric.

Weight ranking mechanism of energy balancing routing metric for RPL protocol in smart grid communications

Recently, the images reconstruction approaches are very essential in digital image processing (DIP), especially in terms of removing the noise contaminations and recovering the content of images. Each image reconstruction approach has different mathematical models. Therefore a performance of individual reconstruction approach is varied depending on several factors such as image characteristic, reconstruction mathematical model, noise model and noise intensity. Thus, this paper presents comprehensive experiments based on the comparisons of various reconstruction approaches under Gaussian and non-Gaussian noise models. The employing reconstruction approaches in this experiment are Inverse Filter, Wiener Filter, Regularized approach, Lucy-Richardson (L-R) approach, and Bayesian approach applied on mean, median, myriad, meridian filters together with several regularization techniques (such as non-regularization, Laplacian regularized, Markov Random Field (MRF) regularization, and one-side Bi-Total Variation (OS-BTV) regularization). Three standard images of Lena, Resolution Chart, and Susie (40th) are used for testing in this experiment. Noise models of Additive White Gaussian Noise (AWGN), Poisson, Salt&Pepper, and Speckle of various intensities are used to contaminate all these images. The comparison is done by varying the parameters of each approach until the best peak-signal-to-noise ratio (PSNR) is obtained. Therefore, PSNR plays a vital parameter for comparisons all the results of individual approaches.

An experimental performance analysis of image reconstruction techniques under both Gaussian and non-Gaussian noise models

Over the last ten years, microelectromechanical systems (MEMS) devices have received attention in many application areas such microwave, wireless, and optical networks. Especially in optical networks, MEMS technology is employed to provide the advantages of large switch matrix size with low loss at an optimum cost [1,2]. Therefore, optical switches based MEMS technology are now widely used and are considered a good option for optical switching networks. Moreover, they also provide wavelength insensitivity, polarization insensitivity, scalability, and very low crosstalk [3-5]. MEMS optical switches provide fast switching speeds ranging from milliseconds to several hundred microseconds. In this article, MEMS-based optical switches are reviewed including their advantages and disadvantages.

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Kornkamol Thakulsukanant

Papers

A novel elementary spatial expanding scheme form on SISR method with modifying geman & mcclure function

An Empirical Evaluation of the Parameters of Trilateral Filter for Noise Removal Implementation on Gaussian and Impulsive Noise

Weight ranking mechanism of energy balancing routing metric for RPL protocol in smart grid communications

An experimental performance analysis of image reconstruction techniques under both Gaussian and non-Gaussian noise models

MEMS Technology for Optical Switching