Reconstruction Distortion Research Articles

Super-resolution spectral reconstruction based on minimum variance frequency estimation and linear fitting

Fourier transform spectroscopy based on the theory of periodogram or maximum entropy spectral estimation may cause spurious peaks or frequency leakage, as well as distortion of the spectral intensity reconstruction. To solve these problems, spectral reconstruction is treated as an estimation of harmonic frequency and intensity in the interferogram, the super-resolution spectral reconstruction method, based on minimum variance spectral estimation and linear fitting (MVLF), is developed and discussed. MVLF is composed of two steps: frequency estimation with minimum variance frequency estimation and spectral intensity reconstruction with linear fitting. For MVLF, the spectral intensity reconstruction accuracy is only related to frequency estimation accuracy. Simulation results of both discrete and continuous spectral reconstruction show that, compared with traditional super-resolution spectral reconstruction methods, MVLF is able to constrain the frequency estimation error within 0.97% and the spectral intensity reconstruction error within 3%.

Spatial Correlation-Based MAC Protocol for Event-Driven Wireless Sensor Networks

W ireless sensor networks is highly spatial correlated . Recently it has been proposed to select a subset of sensors nodes to transmit their data so as to prevent transmission of redundant data. In this paper, we investigate the ways of selecting sensor nod e s and develop a novel sp at ial correlation-based Medium Access Control ( MAC ) protocol for event-driven wireless sensor networks , referred as S C MAC. Based on a theoretical framework, S C MAC adopts priority node selection algorithm and collision avoidance mechanism so that transmission of redundant data is prevented when contending for the shared channel, while SCMAC prioritizes the transmission of route-thru packets. Simulation results show that our protocol achieves higher performance than CC-MAC in the aspect of energy consumption, transmission latency, packet delivery rate , packet drop rate and reconstruction distortion.

Adaptive threshold speech de-noising based on Bark scale wavelet package

When input signal has low Signal-to-Noise Ratio (SNR), the commonly used speech de-noising algorithm will cause distortion for reconstructed signal because of unvoiced sounds weak information losses. In order to overcome this, this paper presented a new method for speech enhancement. Wavelet packet decomposition was used to fit speech critical band, and the voiced and unvoiced sounds were processed separately based on sub-band energy ratio. Then, eight scales of wavelet packet decomposition and four scales of wavelet packet decomposition were employed for the unvoiced and the voiced sounds. A new wavelet adaptive threshold algorithm was obtained based on Bark sub-band, in Bark frequency domain real-time tracking noise level and the adaptive adjustment of coefficient can increase the accuracy of threshold value judgment, and effectively reduces signal reconstruction distortion. The computer simulation results indicate that the new method compared to traditional algorithm has obvious advantages in improving output SNR and effectively reducing the speech distortion. When this new algorithm is combined with spectral subtraction, it can further improve the quality of speech de-noising.

Network Code Design for Orthogonal Two-Hop Network with Broadcasting Relay: A Joint Source-Channel-Network Coding Approach

This paper addresses network code design for robust transmission of sources over an orthogonal two-hop wireless network with a broadcasting relay. The network consists of multiple sources and destinations in which each destination, benefiting the relay signal, intends to decode a subset of the sources. Two special instances of this network are orthogonal broadcast relay channel and the orthogonal multiple access relay channel. The focus is on complexity constrained scenarios, e.g., for wireless sensor networks, where channel coding is practically imperfect. Taking a source-channel and network coding approach, we design the network code (mapping) at the relay such that the average reconstruction distortion at the destinations is minimized. To this end, by decomposing the distortion into its components, an efficient design algorithm is proposed. The resulting network code is nonlinear and substantially outperforms the best performing linear network code. A motivating formulation of a family of structured nonlinear network codes is also presented. Numerical results and comparison with linear network coding at the relay and the corresponding distortion-power bound demonstrate the effectiveness of the proposed schemes and a promising research direction.

Adaptive Power Allocation in Wireless Sensor Networks with Spatially Correlated Data and Analog Modulation: Perfect and Imperfect CSI

We address the problem of power allocation in a wireless sensor network where distributed sensors amplify and forward their partial and noisy observations of a Gaussian random source to a remote fusion center (FC). The FC reconstructs the source based on linear minimum mean-squared error (LMMSE) estimation rule. Motivated by the availability of limited energy in the sensor networks, we undertake the design of power allocation based on minimization of the reconstruction distortion subject to a constraint on the network transmit power. The design is based on the following two cases: (i) exact knowledge of the channel gains and (ii) the estimates of the channel gains. We show that the distortion can be represented as a convex function of the transmit powers of the sensors. Moreover, we show that the power allocation based on this distortion function does not bear any closed form solution. To this end, we propose a novel design based on the successive approximation of the LMMSE distortion, which turns out to be simple, computationally efficient, and exhibits excellent convergence properties. The simulation examples illustrate that the proposed design holds considerable performance gain compared to a uniform power allocation scheme.

Implementation of a novel interpolating method to epicardial potential mapping for atrial fibrillation study

Epicardial potential mapping is an efficient way to visualize the potential distribution on the epicardial surface. We found in our previous study, that the traditional linear interpolation used for the epicardial mapping may cause errors and distortions in reconstruction of the electric activities on the epicardial surface especially during the atrial fibrillation. In this study, we devoted on the implementation of a 3D interpolating method, and verified it in comparison with another interpolating method as well as studying of the mechanism of vagal atrial fibrillation (AF). In case studying, we analyzed the epicardial data from seven canine cardiac models using this method and found the macro-re-entry during the sustainable AF is more likely due to the dispersion of refractoriness in the myocardium and does not demonstrated the focal patterns at the beginning of AF. This indicated that the electrophysiological characteristics of myocardium might have been changed during the paroxysmal atrial fibrillation (PAF).

Optimizing Energy-Efficient Reconstruction of Mobile Point Source in Sensor Networks

To obtain accurate information about the interested physical phenomenon, many nodes should be deployed and collaborated to extract data about the event source. This article proposes a Low Power Self Scheduling protocol for mobile point source reconstruction. The motivation is clear, to provide high level QoS (reconstruction distortion) and reduce energy consumption. This article first obtains a distance to the event source, in which all sensing reports are collected to minimize the reconstruction distortion. This distance is relatively constant under different network densities. Then the mobility of the event source is considered. Sensor nodes are self-scheduled to join or leave the representative nodes group, which guarantee that those appropriate nodes will always be the group member. Simulation validates the effectiveness of the presented scheme.

Surface Geometric and Electronic Structures ofBaFe2As2(001)

BaFe2As2 exhibits properties that are characteristic of the parent compounds of the newly discovered iron (Fe)-based high-T(C) superconductors. By combining real-space imaging of scanning tunneling microscopy and spectroscopy (STM+STS) with momentum-space quantitative low-energy electron diffraction (LEED), we have identified the surface plane of cleaved BaFe2As2 crystals as the As terminated Fe-As layer-the plane where superconductivity occurs. LEED and STM+STS data on the BaFe2As2(001) surface indicate an ordered arsenic (As) terminated metallic surface without reconstruction or lattice distortion. It is surprising that STM images the different Fe-As orbitals associated with the orthorhombic structure, but not the As atoms in the surface plane.

On Rate-Distortion Modeling and Extraction of H.264/SVC Fine-Granular Scalable Video

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> Fine-granular scalable (FGS) technologies in H.264/AVC-based scalable video coding (SVC) provide a flexible foundation to accommodate different network capacities. To support efficient quality extraction, it is important to obtain the rate-distortion (R-D) or Distortion-Rate (D-R) function of each individual picture or a group of pictures (GOP). In this paper, firstly, the R-D function of SVC FGS pictures is analyzed with generalized Gaussian model and the D-R curve is proved to be a concave function overall. Considering the current sub-bitplane technology, the D-R function is revisited and inferred to be linear under MSE criterion within an FGS level, which also explains why the observed D-R curve with PSNR criterion is a piece-wise convex function. Secondly, the drift issue of SVC is analyzed, and a simple and effective distortion model is proposed to estimate the reconstruction distortion with drift error. Thirdly, with the above analysis and models, a virtual GOP concept is introduced, and a new priority setting algorithm is designed to achieve the optimal R-D performance in a virtual GOP. The D-R slope of each FGS packet and the D-R function of each virtual GOP are also obtained during the process. Finally, the D-R slopes of FGS levels are used in quality layer assignment to achieve equivalent coding efficiency to the SVC test model but with significantly reduced complexity. The D-R functions of virtual GOPs are utilized to design a practical method for smooth quality reconstruction. Compared to the prior methods, the smoothed video quality is improved not only objectively but also subjectively. </para>

Optical Sensor for Real-Time Reconstruction of Distortions on Electronically Steered Antenna

A measurement system based on a set of optical fiber probes has been implemented and tested for real-time reconstruction of mechanical distortions of electronically steered antenna arrays. Such an optical sensor allows a full-reconstruction of the emitting surface topography, which is necessary to electronically compensate the degradation of the radiating pattern under mechanical distortions of its structure.

Error-Resilient Multiple Description Coding

In the multiple description coding (MDC), the source is decomposed into two or more descriptions, and then transmitted over on/off channels. At the receiver end, each description can be reproduced with acceptable side distortion; reconstructed signals with lower central distortion can be accomplished by exploiting more descriptions. In order to apply the classical MDC over error-prone channels, we propose error-resilient multiple description coding (ERMDC) to utilize the inherent dependency and redundancy between descriptions to combat bit errors. In this paper, we develop a pair of the ERMDC encoder and central decoder based on the multiple description scalar quantizer (MDSQ). After deriving optimal and suboptimal ERMDC decoders, a novel index assignment algorithm is provided for the ERMDC encoder to improve the error detection capability of the ERMDC decoders. Analytical and experimental results show that the ERMDC outperforms the conventional MDSQ encoder-decoder pair, and achieves lower reconstruction distortions than the side distortion within a large range of bit error rates (BERs).

Shannon's Secrecy System With Informed Receivers and its Application to Systematic Coding for Wiretapped Channels

Shannon's secrecy system is studied in a setting, where both the legitimate decoder and the wiretapper have access to side information sequences correlated to the source, but the wiretapper receives both the coded information and the side information via channels that are more noisy than the respective channels of the legitmate decoder, which in turn, also shares a secret key with the encoder. A single-letter characterization is provided for the achievable region in the space of five figures of merit: the equivocation at the wiretapper, the key rate, the distortion of the source reconstruction at the legitimate receiver, the bandwidth expansion factor of the coded channels, and the average transmission cost (generalized power). Beyond the fact that this is an extension of earlier studies, it also provides a framework for studying fundamental performance limits of systematic codes in the presence of a wiretap channel. The best achievable performance of systematic codes is then compared to that of a general code in several respects, and a few examples are given.

High-fidelity numerical realization of multiple-step Fresnel propagation for the reconstruction of digital holograms

A cascaded Fresnel algorithm for the flexible reconstruction of digital holograms is proposed. Since the fast-Fourier-transform-based numerical realization of the Fresnel integral shows a dependency of its pixel resolution and its computation window size on the propagation distance different from that of the corresponding physical system, the computation window can be smaller than the actual physical diffraction field in the intermediate plane. Consequently, distortions in the final reconstruction may occur. A method is proposed to eliminate such distortion. The validity of this method is shown by both numerical simulations and experimental results.

In-line holographic electron microscopy in the presence of external magnetic fields

It is now a well-known fact that the phase of electron waves is altered by external magnetic fields via the Aharonov–Bohm effect. This implies that any electron interference effects will be to some degree affected by the presence of such fields. In this study we examine the distortion effects of external (constant and variable) magnetic fields on electron interference and holography. For digital holography, the reconstruction of the object is done via numerical calculations and this leaves the door open for correcting phase distortions in the hologram reconstruction. We design and quantitatively assess such correction schemes, which decidedly depend on our knowledge of the magnetic field values in the holographic recording process. For constant fields of known value we are able to correct for magnetic distortions to a great extent. We find that variable fields are more destructive to the holographic process than constant fields. We define two criteria, related respectively to global and local contrast of the hologram to establish the maximum allowed external field which does not significantly hinder the accuracy of in-line holographic microscopy with electrons.

Surface reconstruction and core distortion of silicon and germanium nanowires

We report the results of molecular dynamics simulations for structures of pristine siliconnanowires and germanium nanowires with bulk cores oriented along the [110]direction and bounded by the (100) and (110) surfaces in the lateral direction. Wefound that the (100) surfaces for both silicon and germanium nanowires undergo2 × 1 dimerization while their (110) surfaces do not show reconstruction. The direction of the dimerrows is either parallel or perpendicular to the wire axis depending on the orientation of thesurface dangling bonds. The dimer length for Si is in good agreement with the result obtainedby first-principles calculations. However, the geometry of Si dimers belongs to the symmetrical2 × 1 reconstruction rather than the asymmetrical buckled dimers. We also show that surfacereconstruction of a small nanowire induces significant change in the lattice spacing for theatoms not on the (100) surface, resulting in severe structural distortion of the core of thenanowire.

Model distortions in Bayesian MAP reconstruction

The Bayesian approach and especially the maximum a posteriori (MAP) estimator is most widely used to solve various problems in signal and image processing, such as denoising and deblurring, zooming, and reconstruction. The reason is that it provides a coherent statistical framework to combine observed (noisy) data with prior information on the unknown signal or image which is optimal in a precise statistical sense. This paper presents an objective critical analysis of the MAP approach. It shows that the MAP solutions substantially deviate from both the data-acquisition model and the prior model that underly the MAP estimator. This is explained theoretically using several analytical properties of the MAP solutions and is illustrated using examples and experiments. It follows that the MAP approach is not relevant in the applications where the data-observation and the prior models are accurate. The construction of solutions (estimators) that respect simultaneously two such models remains an open question.

Impact of Data Retrieval Pattern on Homogeneous Signal Field Reconstruction in Dense Sensor Networks

We analyze the impact of data retrieval pattern on the reconstruction performance of a one-dimensional homogeneous random field measured by a large-scale sensor network. From a networking perspective, we connect data retrieval protocols and different sampling schemes. Specifically, we show that the data retrieval pattern affects the efficiency of reconstruction; as the number of received packets M increases, the deterministic retrieval pattern that schedules sensors to transmit from equally spaced locations results in a faster decay of distortion than the random pattern does. In particular, we show that the ratio of the excess reconstruction distortion under the random retrieval pattern to that under the deterministic one grows as logM+O(loglogM). Comparing the reconstruction performance directly, we further show that, in the high measurement signal-to-noise ratio (SNR) regime, the benefit from carefully scheduling sensor transmissions from specific locations instead of collecting in a random fashion is substantial. In the low SNR regime, however, using the random pattern results in little reconstruction performance loss. Finally, as Mrarrinfin, we show the strong convergence property of reconstruction distortion under the random pattern

Aliasing and Reconstruction Distortion in Digital Intermediates

This paper addresses two types of artifacts associated with the image sampling and reconstruction process, namely, aliasing and reconstruction distortion. Aliasing is an artifact that results from sampling a continuous signal at too low of a spatial rate relative to the input frequency content. Shannon's sampling theorem states that discrete sampling of a signal at a uniform rate higher than twice the highest frequency in the signal, called the Nyquist rate, will allow a perfect reconstruction of the original continuous signal. However, image displays do not reconstruct images according to the ideal reconstruction equation, and, in many cases, the display uses nothing more than a sample-and-hold reconstruction. It has long been known that nonideal reconstruction can lead to distortion of the image data at frequencies below the Nyquist rate. Proper recognition of the distinction between aliasing and reconstruction errors can mean the difference between accepting and avoiding artifacts.

MAC Protocols for Optimal Information Retrieval Pattern in Sensor Networks with Mobile Access

In signal field reconstruction applications of sensor network, the locations where the measurements are retrieved from affect the reconstruction performance. In this paper, we consider the design of medium access control (MAC) protocols in sensor networks with mobile access for the desirable information retrieval pattern to minimize the reconstruction distortion. Taking both performance and implementation complexity into consideration, besides the optimal centralized scheduler, we propose three decentralized MAC protocols, namely, decentralized scheduling through carrier sensing, Aloha scheduling, and adaptive Aloha scheduling. Design parameters for the proposed protocols are optimized. Finally, performance comparison among these protocols is provided via simulations.

&amp;lt;tex&amp;gt;$n$&amp;lt;/tex&amp;gt;-Channel Symmetric Multiple Descriptions—Part II: An Achievable Rate-Distortion Region

In this Part II of a two-part paper, we present a new achievable rate-distortion region for the symmetric n-channel multiple-descriptions coding problem (n>2) where the rate of every description is the same, and the reconstruction distortion depends only on the number of descriptions received. Using a new approach for the random coding constructions, along with a generalization of the technique used in the two-channel El Gamal and Cover region to any n, the rate region presented here achieves points that have not been known in the literature previously. This rate region is derived from a concatenation of source-channel erasure codes developed in Part I of this work by deploying the framework of source coding with side information (random binning). The key idea is that by using the framework of source coding with side information, multiple statistically identical realizations representing the coarse version of a source can be simultaneously refined by a single encoding. We point out that there is an important conceptual difference in random coding construction for the multiple-descriptions coding problem between the case of n=2 and n>2. To illustrate the framework, we also present the important case of the Gaussian source in detail.