TV Model Research Articles

Subband PUEA Detection and Mitigation in OFDM-Based Cognitive Radio Networks

This paper considers malicious user detection and energy harvesting in orthogonal frequency division multiplexing-based cognitive radio networks under primary user emulation attack (PUEA). The digital TV (DTV) model adopted is the second generation terrestrial digital television standard (DVB-T2). In this paper, first, we propose an efficient advanced encryption standard (AES)-based DTV scheme, where the existing reference sequence used to generate the P2 pilot symbols in the DVB-T2 frames is encrypted using the AES algorithm to facilitate accurate primary user and malicious user detection. With the proposed scheme, we can detect PUEA accurately over all subcarriers or subbands where the P2 symbols present. Second, we come up with an effective communication scheme for the secondary users (SUs) under PUEA by exploiting the energy harvesting techniques. Optimal power splitting is considered for sum-rate maximization. As the optimal solution relies on multidimensional exhaustive search, we propose an effective suboptimal solution with much lower computational complexity. It is observed that the sum-rate of the SU network can be improved significantly with the energy harvesting technique. Third, we evaluate the worst case PUEA interference in terms of minimizing the sum-rate for the SUs. We show that for practical systems, as channel state information among the SUs is not available to the malicious user, the worst jamming for the SUs is when the malicious user performs equal power allocation over all the white space subcarriers. Simulation results are provided to illustrate the proposed approaches.

Fast Second Degree Total Variation Method for Image Compressive Sensing.

This paper presents a computationally efficient algorithm for image compressive sensing reconstruction using a second degree total variation (HDTV2) regularization. Firstly, a preferably equivalent formulation of the HDTV2 functional is derived, which can be formulated as a weighted L 1-L 2 mixed norm of second degree image derivatives under the spectral decomposition framework. Secondly, using the equivalent formulation of HDTV2, we introduce an efficient forward-backward splitting (FBS) scheme to solve the HDTV2-based image reconstruction model. Furthermore, from the averaged non-expansive operator point of view, we make a detailed analysis on the convergence of the proposed FBS algorithm. Experiments on medical images demonstrate that the proposed method outperforms several fast algorithms of the TV and HDTV2 reconstruction models in terms of peak signal to noise ratio (PSNR), structural similarity index (SSIM) and convergence speed.

O fim da televisão, um fim ou um recomeço?

Resumo:O livro O Fim da Televisão revisita autores como Manuel Castells, Mario Carlón, Eliseo Verón, Carlos Scolari, Henry Jenkins, entre outros, com o intuito de atualizar algumas das principais discussões acerca do papel da TV no cenário atual. Questões como o implemento de dispositivos midiáticos móveis, as novas formas de consumo das produções audiovisuais, a multiplicação das telas e a interatividade do espectador, são levantadas como prognósticos do fim de um modelo de TV broadcasting, ao mesmo tempo que aponta a relação dos destinatários com os novos meios como ainda mediada pela linguagem herdada do modelo de TV tradicional.

A Sobel-TV based Hybrid Model for De-noising Remote Sensing Image with Gaussian and Salt-pepper Noise

The pre-processed remote sensing images are often polluted by Gaussian and salt-pepper noises. In order to solve this problem, a Sobel-TV based hybrid model is proposed to de-noise the pre-processed remote sensing images. It uses TV model to de-noise and uses Sobel algorithm to control smoothness of the image’ edge. This proposed method will not only efficiently remove image noise but also simultaneously reserves detail information such as edge and texture. Experimental results show the proposed algorithm achieves better SNR and SSIM compared with other methods. In terms of visual quality, the proposed algorithm can remove the noise of the images and preserve more details, which is important value to preprocess remote sensing image.

基于TV模型的暗原色理论雾天图像复原算法

基于TV模型的暗原色理论雾天图像复原算法

A new nonlocal variational setting for image processing

We introduce a new nonlocal variational scheme for image denoising. This scheme is motivated by, but different from the nonlocal means filter of Buades et al [9] and the nonlocal TV model proposed by Gilboa-Osher by using nonlocal operators. Our approach is based on general geometric considerations. Experiments show that the corresponding TV model yields denoising results that can compare favorably with those obtained by other methods.

Цифровые технологии в телевидении и трансформация медиарынка

The article analyzes new phenomena in the field of television associated with the digital era, in particular, the transformation of media market under the influence of technological, economic, financial and institutional factors of digitalization. Contemporary international and Russian television industry is in the process of digital revolution. The era of traditional television as a typical broadcasting technology, a traditional social, economic and cultural phenomenon, has come to an end. We are on the verge of a global and irrevocable shift to mass utilization of various digital devices that certainly affect the positions of television as a separate industry. Modern television is outlined as a part of a wide digital media market, just a segment of a highly competitive entertainment structure with complex network interactions. In terms of Russia, the new phenomena accompanying the evolution of media and television markets in the process of digitalization urgently need an economic analysis. In what direction is it necessary to develop the local broadcasting? Is there a sound commercial future of national and regional television companies? What lessons can extract Russia from world experience? What else does Russian television need to improve efficiency and global competitiveness? These issues are detail considered in the article. Trends and obstacles for the implementation of a prospective business model for Russian TV are shown. It is concluded that successful development of the Russian television industry is possible only under the conditions of efficient formation of a fundamentally new configuration of a multi-market structure type.

The Jump Set under Geometric Regularization. Part 1: Basic Technique and First-Order Denoising

Let $u \in \mbox{BV}(\Omega)$ solve the total variation denoising problem with $L^2$-squared fidelity and data $f$. Caselles et al. [Multiscale Model. Simul. 6 (2008), 879--894] have shown the containment $\mathcal{H}^{m-1}(J_u \setminus J_f)=0$ of the jump set $J_u$ of $u$ in that of $f$. Their proof unfortunately depends heavily on the co-area formula, as do many results in this area, and as such is not directly extensible to higher-order, curvature-based, and other advanced geometric regularisers, such as total generalised variation (TGV) and Euler's elastica. These have received increased attention in recent times due to their better practical regularisation properties compared to conventional total variation or wavelets. We prove analogous jump set containment properties for a general class of regularisers. We do this with novel Lipschitz transformation techniques, and do not require the co-area formula. In the present Part 1 we demonstrate the general technique on first-order regularisers, while in Part 2 we will extend it to higher-order regularisers. In particular, we concentrate in this part on TV and, as a novelty, Huber-regularised TV. We also demonstrate that the technique would apply to non-convex TV models as well as the Perona-Malik anisotropic diffusion, if these approaches were well-posed to begin with.

Smart TV-Smartphone Multiscreen Interactive Middleware for Public Displays.

A new generation of public displays demands high interactive and multiscreen features to enrich people's experience in new pervasive environments. Traditionally, research on public display interaction has involved mobile devices as the main characters during the use of personal area network technologies such as Bluetooth or NFC. However, the emergent Smart TV model arises as an interesting alternative for the implementation of a new generation of public displays. This is due to its intrinsic connection capabilities with surrounding devices like smartphones or tablets. Nonetheless, the different approaches proposed by the most important vendors are still underdeveloped to support multiscreen and interaction capabilities for modern public displays, because most of them are intended for domestic environments. This research proposes multiscreen interactive middleware for public displays, which was developed from the principles of a loosely coupled interaction model, simplicity, stability, concurrency, low latency, and the usage of open standards and technologies. Moreover, a validation prototype is proposed in one of the most interesting public display scenarios: the advertising.

Exponential total variation model for noise removal, its numerical algorithms and applications

The total variation model has been considered to be one of the most successful and representative denoising models that can preserve edges well. However, its main shortage is that it frequently causes the undesirable “block” effect. To solve this problem, high-order TV models have been proposed. Yet, they tend to damp the high frequency components in an image, often resulting in over smoothing or blurring of main features in an image. Besides, the optimization solutions underlying high-order TV models can only be obtained through numerically solving the associated high-order PDEs derived from the Euler–Lagrange equation, which is quite time-consuming. In this paper, we propose a novel total variation model based on exponential function (ETV). Furthermore, a fast numerical algorithm is designed for ETV based on Split Bregman algorithm. We test our ETV on a broad range of standard images, synthetic aperture radar (SAR) image and medical magnetic resonance images (MRI), and compared with the related TV, and high-order TV models. The experimental results have demonstrated that our ETV offers much better trade-off between noise removal and edge preservation as compared with TV and high-order TV models. In addition, ETV also shows a high computational efficiency when boosted by split Bregman algorithm.

Image inpainting algorithm based on TV model and evolutionary algorithm

With the development of modern image processing techniques, the numbers of images increase at a high speed in network. As a new form of visual communication, image is widely used in network transmission. However, the image information would be lost after transmission. In view of this, we are motivated to restore the image to make it complete in an effective and efficient way in order to save the network bandwidth. At present, there are two main methods for digital image restoration, texture-based method and non-textured-based method. In the texture-based method, Criminisi algorithm is a widely used algorithm. However, the inaccurate completion order and the inefficiency in searching matching patches are two main limitations of Criminisi algorithm. To overcome these shortcomings, in this paper, an exemplar image completion based on evolutionary algorithm is proposed. In the non-textured-based method, total variation method is a typical algorithm. An improved total variation algorithm is proposed in this paper. In the improved algorithm, the diffusion coefficients are defined according to the distance and direction between the damaged pixel and its neighborhood pixel. Experimental results show that the proposed algorithms have better general performance in image completion. And these two new algorithms could improve the experience of network surfing and reduce the network communication cost.

BALLOON-EXPANDABLE STENTS EXPANSION IN TAPERED VESSELS AND THEIR INTERACTIONS

In-stent restenosis (ISR) after stent implantation, especially in tapered vessels, remains an obstacle in the long-term benefits of stenting. In the present study, a finite element method (FEM) was employed to investigate the expansion process of balloon-expandable stents in tapered vessels (the TV model) and their interactions. For comparison, a numerical model of the same stent deployment in a straight vessel was also investigated. Results showed that in the TV model, the peak tissue stresses took place at the distal end of the tapered vessel. The node displacements of the stent's proximal and distal ends remained consistent before the stent contacted the tapered vessel, while the proximal end was larger than the distal end after the stent contacted the tapered vessel. The regions of maximum stresses in the stent after expansion were concentrated in the corners of the diamond cells of the stent's proximal end. The investigation provided some interpretations of the clinical observations in tapered vessels and also provided stent design proposals for tapered vessels. The FEM quantified the mechanical properties of stents in tapered vessels, and can help clinicians select appropriate stents, assist designers in pretests and create new stents made especially for tapered vessels.

A total variation model based on edge adaptive guiding function for remote sensing image de-noising

The unexpected noise generated during the process of remote sensing images formation and transmission process is a main factor undermining the images’ quality and usage. In recent years, thanks to its local self-adapting characteristics, formal normalization, and modeling flexibility, PDE has received wide attention for its image de-noising functions, thus pushing the realization of maintaining image details while successfully de-noising a new goal for remote sensing images filtering. Having firstly analyzed and discussed the TV model and M model, a modified variation-model (S model for short) based on edge adaptive guiding function is proposed in this paper. The model introduces edge adaptive guiding function based on the standard gradient into the non-linear diffusion term and re-constructed approaching term, which adaptively adjust the smooth intensity around edge and texture information-rich regions of remote sensing images. S-model does not only overcome staircase effect that is easily produced in the TV model, but also avoids losing details and texture information which is often seen in M model, it can efficiently eliminate noises, maintain a good image edge and keep texture details perfectly. The experimental results validate the effectiveness and stability of the proposed model.

Application of array microphone measurement for the enhancement of sound quality by use of adaptive time reversal method

The purpose of this research is to develop an algorithm which can be used in the system of speech recognition. In the previous research, a target signal can be reconstructed by a signal separation technique which is based on time-reversal method (TRM) via self-focusing property. In this research, a multiple signal separation technique which is based on adaptive time-reversal method (ATRM) is developed. The advantage of ATRM is to reconstruct target signal and to cancel noise signals simultaneously if impulse response functions of environment between target source, noise sources, and array microphone are known. In the simulation, correlation coefficient and signal to noise ratio (SNR) are implemented as indicators to evaluate the performance of signal separation for TRM and ATRM in a reverberation room, and to investigate the differences between two methods. The comparison indicates that number of array microphone is significantly reduced from 14-microphones via TRM to 6-microphones via ATRM. Furthermore, the experiments of signal separation are conducted to a model of smart TV with multiple noise sources in the environment. Finally, a real time system of signal separation was developed. All the results indicate that the target of source was clearly reconstructed with enhancing of correlation coefficient and SNR by using ATRM.

Fullbore Image Construction of Imaging Logging Based on the Improved Texture Inpainting Method

The image inpainting method based on CriminiciA’s algorithm is slowly complete the image for large blank area. An improved algorithm based on the classic texture synthesis algorithm for image inpainting is proposed for imaging logging inpainting, which is used to generate the fullbore image. Two schemes, the local search method and priority calculation with TV model, are employed in the improved texture synthesis method. Some examples were given to demonstrate the effectiveness of the proposed algorithm on dealing with fullbore image construction with large blank area and raising efficiency obviously.

Total Variation Differential Equation with Wavelet Transform for Image Restoration

To overcome the staircasing effects and simultaneously avoid edge blurring, We present an adaptive partial differential equation combining the total variation with wavelet transform for image restoration. A noise removal algorithm based on variation method and partial difference equations is proposed in this paper. The combining algorithm takes the advantage of both filters since it is able to preserve edges while avoiding the staircase effect in smooth regions. The TV method provides fast adaptive wavelet-based solvers for the TV model. Our approach not only employs a wavelet collocation method applied to the TV model using two-dimensional anisotropic tensor product of wavelets, but also proposes the differential equation for image restoration. Most conventional image processors consider little the influence of human vision psychology. The algorithm inherently not only combines the restoration property of wavelet compression algorithms with that of the TV model, but also gives a relative new TV functional which considers the influence of human vision psychology. We present a detailed description of our method which indicates that a combination of wavelet based restoration techniques with the TV model produces superior results. Experimental results illustrate the effectiveness of the model image restoration. DOI : http://dx.doi.org/10.11591/telkomnika.v12i6.5495 Full Text: PDF

Manufacturing Image in Painting Based on Partial Differential Equations

For TV model, repair algorithm only along the gradient perpendicular to the direction of diffusion that will cause staircase effect, iterative low efficiency and generate false edge of the shortcomings. The article improved K and P parameters of manufacturing image restoration algorithm. The algorithm contains both isotropic and anisotropic diffusion, taking regional frequency difference realized in different areas using different iterative equation. The experimental results show that the algorithm is compared with the TV model algorithm has the same restorative effects, avoid the staircase effect and better than the TV model repair speed.

An Automatic Image Inpainting Algorithm Based on FCM

There are many existing image inpainting algorithms in which the repaired area should be manually determined by users. Aiming at this drawback of the traditional image inpainting algorithms, this paper proposes an automatic image inpainting algorithm which automatically identifies the repaired area by fuzzy C-mean (FCM) algorithm. FCM algorithm classifies the image pixels into a number of categories according to the similarity principle, making the similar pixels clustering into the same category as possible. According to the provided gray value of the pixels to be inpainted, we calculate the category whose distance is the nearest to the inpainting area and this category is to be inpainting area, and then the inpainting area is restored by the TV model to realize image automatic inpainting.

A Sobel-TV Based Hybrid Model for Robust Image Denoising

The traditional Total-Variation algorithm has a good result to de-noise for noise image of small scale details, but it easily losses the details for the image with rich texture and tiny boundary. In order to solve this problem, this paper proposes a Sobel-TV model algorithm for image denoising. It uses TV model to de-noise and uses Sobel algorithm to control smoothness of image, which not only efficiently removes image noise but also simultaneously retail information, such as edge and texture. The experiments demonstrate that the proposed algorithm is simple, practical and generates better SNR, which is an important value to preprocess image.

On Optimal Functioning of the Aeolian Electro-Power Systems

The paper approaches the possibility of power functioning of the Aeolian systems. Power Aeolian systems, due to high inertia moments and rapid variation in time of the wind speed cannot constantly function on the maximum power point. Therefore it must be considered the matter of determining the optimal functioning speed of the Aeolian device on the basis of evaluating the momentary wind speed in order to get maximum of electric power. The calculation is based upon an original mathematical model for the wind turbine TV and an experimental direct follow of the wind speed in time. Actually, it is presented the way of loading the generator according to the wind speed.etc.