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

In 2010, the DBAMF (decision based adaptive median filter) denoising method based on ROAD that was proposed for eradicating an impulsive noise because ROAD (Rank Order Absolute Difference) has the obviously high performance in noisy classification and is mathematically developed from similar measurement method in computer vision for identifying whether the pixel is contaminated by impulsive noise or the noise-free. For that reason, the scholar thesis article intents to inspect the performance of the denosing method implemented by DBAMF for RVIN (Random Value Implosive Noise) condition. For inspecting the performance and its impediment of the DBAMF denoising method, the two worldwide assessment images integrated of Girl and Airplane has been manipulated in these performance inspections under RVIN condition by originally denigrated by accumulating the RIVN at generous power. Later, every denigrated image is enhanced by the denosing method implemented by DBAMF. For indicating the DBAMF performance, the classical SMF (Standard Median Filter) and AMF (Adaptive Median Filter) are comparatively integrated in this performance inspection.

Performance Inspection of Denoising Method Implemented by Decision Based Adaptive Median Filter for Using under RVIN Condition

Since 1998, the Bilateral filter (BF) has been proposed for suppressing Gaussian noise however the BF cannot functionally perform under the mix noise (that is comprised of Gaussian and S&P noise). Thereby, the Trilateral filter (TF) that is an adapted BF formed on the ROAD (Rank-Ordered Absolute Differences) technique was initially stated by Roman Garnett et al. for self-regulating suppressing and eliminating of the mix noise in 2005. This paper analytically investigates the dissection capability consequence of 4 parameters (joint impulsivity variance, ROAD variance, spatial variance and radiometric variance) of the TF for suppressing several mixed noise circumstances. In this paper, five contaminated images (Lena, Girl-Tiffany, Mobile, Baboon, House) under many mixed Gaussian and S&P noise circumstances are used to investigate the maximum TF capability in the PSNR aspect, contemplated with the ordinary techniques: median filter, mean filter and BF (BF). Later, the dissection analytical value of joint impulsivity variance and ROAD variance that make the highest PSNR is investigated for each image and each mix noise case.

Dissection capability analysis of noise suppression technique utilizing trilateral filter under mixed noise circumstances

Commonly, filtering technique and the video registration technique are two main significance factors of a video SR (Super Resolution) enhancement algorithm. First, the classical filtering technique is based on a linear filter such as mean or median filter that are only suitable for noiseless or low power noise. Later, classical video registration techniques are usually based on a simple translation model because of the fast computation and easy implementation thereby this registration has high precision error. To get over both problems, this paper proposed the alternative SR spatial enhancement using adaptive meridian filter and GOM (General Observation Model) registration for severe noisy blurred videos. The adaptive meridian filter is a robust filter, which is desire for controlling high power outlier, and GOM is a high precision registration technique, which is desired for registering a fast spatial sequence. For proving the proposed performance, the simulated experiments are done in several environments as following: 1. Additive White Gaussian Noise (AWGN) at SNR=15, 17.5, 20, 22.5, 25dB; 2. Poisson Noise; 3. Multiplicative White Gaussian Noise (Speckle Noise) at V=0.01, 0.02, 0.03; 4. Salt and Pepper Noise at D=0.005, 0.010, 0.015. The proposed enhancement algorithm shows that the PSRN of the enhanced image is higher than the SR spatial enhancement based on classical filter with classical registration and GOM registration.

An alternative SR spatial enhancement based on adaptive meridian filter and GOM registration for severe noisy blurred videos

This paper proposes a novel denoising technique for suppressing a random-valued impulse noise. At first, the proposed noise detection is based on determining the optimum direction, by estimating the Standard Deviation (SD) in different eight directions of the filtering window. Next, the similarity index is estimated by average Absolute Difference (AD) for comparing of how close the processed pixel is to its neighbors in the optimum direction. Later, the processed pixel is noiseless if the similarity index is low value otherwise the processed pixel is noisy pixel. Comprehensive results verify that the proposed technique is exceptional efficiency than other previous denoising techniques at all noise rates.

The Novel Denoising Technique Based on 8D Optimal Directions Using Statistical SD for Random-Valued Impulse Noise

Due to statistical characteristic, ROAD (Rank Order Absolute Difference) is one of the highest similar measurement performance in digital image for recognizing whether the impulsive noise pixel or the non-impulsive noise pixel whence the DBAMF (decision based adaptive median filter) was invented for suppressive an impulsive noise in 2010. As a result, the dissertation article aim to scrutinize the performance of the noise suppressing technique based on DBAMF under S&P noise. For evaluating the performance and its limitation of the noise suppressing technique based on DBAMF, the two assessment digital images constituted of Lena and Pepper are exploited in these simulation evaluations under SPN by initially disparaged by adding the impulsive noise (or SPN) at plentiful quantity. Next, each disparaged digital image is refined by the noise suppressing technique based on DBAMF. Moreover, the refined image is confronted with the refined image from the classical SMF (Standard Median Filter) and AMF (Adaptive Median Filter) for proving the DBAMF performance from quantitative indicator perspective.

Kornkamol Thakulsukanant

Papers

Performance Inspection of Denoising Method Implemented by Decision Based Adaptive Median Filter for Using under RVIN Condition

Dissection capability analysis of noise suppression technique utilizing trilateral filter under mixed noise circumstances

An alternative SR spatial enhancement based on adaptive meridian filter and GOM registration for severe noisy blurred videos

The Novel Denoising Technique Based on 8D Optimal Directions Using Statistical SD for Random-Valued Impulse Noise

Simulation Evaluation of Noise Suppressing Technique Based on Decision Based Adaptive Median Filter for Salt&Pepper Noise