Abstract: Array cameras in accordance with embodiments of the invention perform super resolution processing using images of a scene that contain aliasing. In several embodiments, the depth of pixels is determined by fusing portions of a higher resolution image at a number of hypothesized depths and determining the depth at which the portion of the higher resolution image best matches the scene captured in the lower resolution images used to fuse the higher resolution image.

Abstract: Aliasing is a common artifact in low-resolution (LR) images generated by a downsampling process. Recovering the original high-resolution image from its LR counterpart while at the same time removing the aliasing artifacts is a challenging image interpolation problem. Since a natural image normally contains redundant similar patches, the values of missing pixels can be available at texture-relevant LR pixels. Based on this, we propose an iterative multiscale semilocal interpolation method that can effectively address the aliasing problem. The proposed method estimates each missing pixel from a set of texture-relevant semilocal LR pixels with the texture similarity iteratively measured from a sequence of patches of varying sizes. Specifically, in each iteration, top texture-relevant LR pixels are used to construct a data fidelity term in a maximum a posteriori estimation, and a bilateral total variation is used as the regularization term. Experimental results compared with existing interpolation methods demonstrate that our method can not only substantially alleviate the aliasing problem but also produce better results across a wide range of scenes both in terms of quantitative evaluation and subjective visual quality.

Abstract: In a computer system having virtual machines, one or more unused bits of a guest virtual address range are allocated for aliasing so that multiple virtually addressed sub-pages can be mapped to a common memory page. When one bit is allocated for aliasing, sub-pages can be virtually addressed at a granularity that is one-half of a memory page. When M bits are allocated for aliasing, sub-pages can be virtually addressed at a granularity that is 1/(2M)-th of a memory page. The granularity of page sizes can be selected according to particular use cases. In the case of COW optimization, page sizes can be set statically between 4 KB and 2 MB or configured dynamically among multiple page sizes.

Abstract: Database management and security is implemented in a variety of embodiments. In one such embodiment, data sets containing sensitive data elements are analyzed using aliases representing sensitive data elements. In another embodiment, the sensitive data elements are stored in an encrypted form for use from a secure access, while the alias is available for standard access.

Abstract: We describe a new simultaneous source separation algorithm using frequency-diverse filtering. The method combines the array response at different frequencies to suppress spatial aliasing and converts the data separation problem into a one-norm (l1) or zero-norm (l0) optimization problem. Synthetic and field data tests show that the algorithm works well with both spatially aliased and unaliased data. The method requires further work to reduce the computation cost.

Abstract: We define a novel static analysis for Java bytecode, called definite expression aliasing. It infers, for each variable v at each program point p, a set of expressions whose value at p is equal to the value of v at p, for every possible execution of the program. Namely, it determines which expressions must be aliased to local variables and stack elements of the Java Virtual Machine. This is a useful piece of information for a static analyzer, such as Julia, since it can be used to refine other analyses at conditional statements or assignments. We formalize and implement a constraint-based analysis, defined and proved correct in the abstract interpretation framework. Moreover, we show the benefits of our definite expression aliasing analysis for nullness and termination analysis with Julia.

Abstract: This thesis presents an analysis of systematic error in full-field amplitude modulated continuous wave range-imaging systems. The primary focus is on the mixed pixel/multipath interference problem, with digressions into defocus restoration, irregular phase sampling and the systematic phase perturbations introduced by random noise. As an integral part of the thesis, a detailed model of signal formation is developed, that models noise statistics not included in previously reported models. Prior work on the mixed pixel/multipath interference problem has been limited to detection and removal of perturbed measurements or partial amelioration using spatial information, such as knowledge of the spatially variant scattering point spread function, or raytracing using an assumption of Lambertian reflection. Furthermore, prior art has only used AMCW range measurements at a single modulation frequency. In contrast, in this thesis, by taking multiple measurements at different modulation frequencies with known ratio-of-integers frequency relationships, a range of new closed-form and lookup table based inversion and bounding methods are explored. These methods include: sparse spike train deconvolution based multiple return separation, a closed-form inverse using attenuation ratios and a normalisation based lookup table method that uses a new property we term the characteristic measurement. Other approaches include a Cauchy distribution based model for backscattering sources which are range-diffuse, like fog or hair. Novel bounding methods are developed using the characteristic measurement and attenuation ratios on relative intensity, relative phase and phase perturbutation. A detailed noise and performance analysis is performed of the characteristic measurement lookup table method and the bounding methods using simulated data. Experiments are performed using the University of Waikato Heterodyne range-imager, the Canesta XZ-422 and the Mesa Imaging Swissranger 4000 in order to demonstrate the performance of the lookup table method. The lookup table method is found to provide an order of magnitude improvement in ranging accuracy, albeit at the expense of ranging precision.

Abstract: Sharing mutable objects can result in broken invariants, exposure of internal details, and other subtle bugs. To prevent such issues, it is important to control accessibility and aliasing of objects. Dynamic Ownership is an effective way to do so, but its owner-as-dominator discipline is too restrictive: objects are either accessible or not. We propose in this paper to control accessibility and aliasing with more flexibility using two mechanisms, filters and crossing handlers. We demonstrate the benefits of the flexibility offered by these mechanisms, and report on the adaptation of a Smalltalk web server with our approach. We conclude that our variant of dynamic ownership is flexible enough to accommodate an existing design, while at the same time constraining it enough to highlight design anomalies.

Abstract: A Shack-Hartmann wavefront sensor samples the wavefront in the pupil. The wavefront shape will be undersam­ pled, since although the wavefront average spatial spectrum is a rapidly decreasing function of spatial frequency, it contains frequencies higher than the Nyquist limit : this well-known phenomenon is known as aliasing. The impact of aliasing in adaptive optics is difficult to estimate. Some methods have been proposed, that aim at optically filter out high wavefront frequencies ; some authors gave an estimate of this error, but most of the time these estimations are based on Monte-Carlo simulations of wavefront sensor. We propose in this paper an analytical study of the aliasing effect, and study how the aliasing error distributes over temporal frequencies. An analytical expression of the temporal spectrum of the aliasing error maybe of importance for system modeling or performance prediction in adaptive optics.

Abstract: A system and method for generating an m-dimensional signature vector with aliasing across synonyms in a computing device is provided. Data representable by a plurality of key-value pairs, each comprising a unique identifier and an associated non-zero value of n-dimensional data is received at the computing device. Elements of the m-dimensional aliased signature vector are generated using synonym information of keys from the plurality of key-value pairs.

Abstract: Systems, methods and computer program products for aliasing of named data objects (in named data networks) and entities for named data networks (e.g., named graphs for named data networks). In various examples, aliasing of named data objects may be implemented in one or more named data networks in the form of systems, methods and/or algorithms. In other examples, named graphs may be implemented in one or more named data networks in the form of systems, methods and/or algorithms.

Abstract: The algebraic method provides useful techniques to identify models in designs and to understand aliasing of polynomial models. The present

Abstract: Method and apparatus to efficiently detect violations of data dependency relationships. A memory address associated with a computer instruction may be obtained. A current state of the memory address may be identified. The current state may include whether the memory address is associated with a read or a store instruction, and whether the memory address is associated with a set or a check. A previously accumulated state associated with the memory address may be retrieved from a data structure. The previously accumulated state may include whether the memory address was previously associated with a read or a store instruction, and whether the memory address was previously associated with a set or a check. If a transition from the previously accumulated state to the current state is invalid, a failure condition may be signaled.

Abstract: The combination of mutable state and pointer aliasing is often troublesome due to non-obvious (and usually unspecified) interferences that may occur between non-local parts of the program. We present a type-based approach to statically control aliasing and mutable state in a minimalistic single-threaded procedural language with support for structures and references. By introducing views, re-combinable typestate-centric abstractions that encode both type structure and permission, we are able to handle shared and unique references in a way that statically ensures that no destructive interferences may occur during execution. We furthermore provide novel information hiding mechanisms, view declarations and view equations, that modularly define abstract constraints describing how these views can be split/merged to manage a program’s permission flow. We adapt the concept of rely-guarantee to create a flexible scheme for handling shared structures where each reference guarantees it will produce a certain state and relies on the other references limiting their changes to a certain state space. Similarly, by means of a focus operation, we are able to have intermediate (but not externally visible) states that temporarily break away from the guaranteed condition, allowing additional flexibility without violating safety. By unifying state and aliasing control into a single abstraction, view typestate, we believe we can provide a simpler and more intuitive programming model that captures the main effects of stateful computations in a single-threaded environment.

Abstract: INTRODUCTION A new MRI acceleration technique, referred to as RATE, which relies on a new concept of k-space aliasing, is introduced. RATE uses tailored excitation modules consisting of RF pulses and gradients to deliberately overlap distinct k-space points. This accelerates a scan as all k-space points in a time frame can now be sampled in a time span shorter than that of a full acquisition. RATE uses the RF excitation pulses to tag the overlapped points that are then resolved through Fourier transformation in time. K-space signal can either have a narrow spectrum because they come from features that are non-dynamic [1] or because they come from structures that have weak signal magnitude. In the latter case, the temporal spectrum may not be narrow but only a small portion remains relevant as the rest remains under noise. RATE exploits these properties through a targeted allocation of temporal bandwidth such that the bandwidth assigned to central k-space is much higher than that assigned to the edges. When used with Parallel Imaging [2,3] (PMRI), the total acceleration will be ARATE*APMRI where APMRI is PMRI acceleration and ARATE is RATE acceleration. THEORY

Abstract: Sampling and aliasing : as modern video technology is digitally represented, an understanding of sampling and sample rates is needed. Sampling occurs in both spatial and temporal dimensions, and aliasing can lead to video artifacts, discussed in later chapters.

Abstract: PROBLEM TO BE SOLVED: To solve the problem in which: when video encoding is performed, processing such as reduction of the screen size of video prior to the video encoding and enlargement of the screen size of the video after video decoding is performed in some cases; it is necessary to use a low-pass filter having a filter characteristic for removing an aliasing noise part in an application not permitting aliasing noise; but, input video encoding information does not have information on aliasing noise, so that it cannot be determined what type of filter processing is to be performed.SOLUTION: The presence/absence of aliasing noise and the maximum value and the minimum value of a contained band are contained in video information and transmitted. According to the present invention, for example, use of information on aliasing noise transmitted after video decoding enables an influence of aliasing noise to be estimated and the aliasing noise to be removed using a low-pass filter as necessary.

Abstract: As software systems rise in size and complexity, the need for verifying some of their properties increases. One important property to be verified is the resource usage, i.e. how many resources the program will need for its execution, where resources include execution time, memory, power, etc. Resource usage analysis is important in many areas, in particular embedded systems and cloud computing. Thus, resource analysis has been widely researched and some different approaches to this have been proposed based in particular on recurrence solving, abstract interpretation and amortised analysis. In the amortised analysis technique, a nonnegative number, called potential, is assigned to a data structure. The amortised cost of operations is then defined by its actual cost plus the difference in potential of the data structure before and after performing the operation. Amortised analysis has been used for automatic resource analysis of functional and object-oriented programs. The potentials are defined using refined types and typing rules then ensure that potential and actual resource usage is accounted for correctly. The automatic inference of the potential functions can then be achieved by type inference. In the case of functional programs, the structure of the types is known. Thus, type inference can be reduced to solving linear arithmetic constraints. For object-oriented programs, however, the refined types are more complicated because of the general nature of objects: they can be used to define any data structure. Thus, the type inference must discover not only the potential functions for the data structure but also the data structures themselves. Other features of object-oriented programs that complicate the analysis are aliasing and imperative update. Hofmann and Jost presented in 2006 a type system for amortised heap-space analysis of object-oriented programs, called Resource Aware JAva (RAJA). However, they left the problem of type inference open. In this thesis we present a type inference algorithm for the RAJA system. We were able to reduce the type inference problem to the novel problem of satisfiability of arithmetic constraints over infinite trees and we developed a heuristic algorithm for satisfiability of these constraints. We proved the soundness of the type inference algorithm and developed an OCaml implementation and experimental evaluation that shows that we can compute linear upper-bounds to the heap-space requirements of many programs, including sorting algorithms for lists such as insertion sort and merge sort and also programs that contain different interacting objects that describe real-life scenarios like a bank account. Another contribution of this thesis is a type checking algorithm for the RAJA system that is useful for verifying the types discovered by the type inference by using the \emph{proof carrying code} technology.

Abstract: A method is provided for providing a 3D image data record relating to a biological object with suppressed aliasing artifacts overlapping the field of view caused by an incomplete geometric capture of the object by a computed tomography. A first 3D image data record is provided to describe a subarea of the object. A second 3D image data record is obtained by the computed tomography including data relating to the subarea of the object and is registered with the first 3D image data record. Data of the second 3D image data record is extended and/or amended according to data of the first 3D image data record. A part of such data of the second 3D image data record can be assigned to an aliasing artifact overlapping the field of view and thus generates a modified second 3D image data record with suppressed aliasing artifacts overlapping the field of view.

Abstract: In this paper we revisit the problem of blue noise sampling with a strong focus on the spectral behavior of the sampling patterns. We use the mathematical relationship between the radial power spectrum and the radial distribution function to synthesize two types of blue noise patterns: ideal blue noise patterns that have a power spectrum in form of a step function and produce almost no coherent aliasing, and effective blue noise patterns that have a high effective Nyquist frequency and produce a controlled amount of aliasing. We give a definition for this effective Nyquist frequency in stochastic sampling and propose an error metric that characterizes the amount and spectral distribution of aliasing. We show that our blue noise sets avoid most of the artifacts caused by oscillations in the power spectra of existing blue noise patterns. Finally, we present a new algorithm for constructing point sets with a given power spectrum.

Abstract: The invention discloses a two-dimensional image anti-aliasing method and a device thereof, which pertain to the technical field of rasterized image processing and solve the problems of aliasing situation and not quite high printing quality when printing documents in the prior art. The two-dimensional image anti-aliasing method comprises the steps as follows: the boundary information of a two-dimensional image on a page layout and the corresponding rasterization data of the page layout are obtained; pixel points which are adjacent to the boundary points of the two-dimensional image but not boundary points are found in the rasterization data according to the boundary information; and transition points are added to the pixel points to smooth aliasing. The device comprises: an obtaining unit used for obtaining the boundary information of the two-dimensional image on the page layout and the corresponding rasterization data of the page layout; a searching unit used for finding out the pixelpoints which are adjacent to the boundary points of the two-dimensional image but not boundary points in the rasterization data according to the boundary information; and an adding unit used for adding the transition points to the pixel points to smooth the aliasing.

Abstract: Plotkin's structural operational semantics provides a tried and tested method for defining the semantics of a programming language via sets of rules that define valid transitions between program configurations. Mosses' modular structural operational semantics (MSOS) recasts the approach by making use of rules consisting of labelled transitions, allowing a more modular approach to defining language semantics. MSOS can be adapted by using "syntactic" labels that allow local variables and aliasing to be defined without augmenting the semantics with environments and locations. The syntactic labels allow both state-based constructs of imperative languages and event-based constructs of process algebras to the specified in an integrated manner. To illustrate the integrated approach we compare its rules with Plotkin's original rules for both small-step and big-step operational semantics. One issue that arises is that defining concurrency requires the use of a small-step approach to handle interleaving, while defining a specification command requires a big-step approach. The integrated approach can be generalised to use a sequence of (small) steps as a label; we call this a multi-step operational semantics. This approach allows both concurrency and non-atomic specification commands to be defined.

Abstract: Purely reactive systems have been used in many robotics researches. However, they have difficulty in solving the hidden state problems. Internal memory has been used to solve the hidden state problems, which is also called the perceptual aliasing problems. Woods problem is one of the perceptual aliasing problems. In this paper, we apply two methods, Finite State Machine and GP-automata controllers, to solve the Woods problem. These two methods are compared in terms of the behavior performance of the agents with internal memory and sensor states. The performance of each method in the Woods problem is measured by the average number of time steps needed to reach a goal position from all possible initial positions. The analysis of the memory shows that both memory states and sensor states affect the behavior performance of the agent.

Abstract: The invention provides a scanning conversion method used in color ultrasound imaging, which comprises a storage step, a coordinate conversion step, and an interpolation step; wherein, the interpolation step comprises a neighbor point inner interpolative substep, an aliasing determination substep and an echo data revision substep. The interpolation treatment is carried out on neighbor point ultrasound echo data by the neighbor point inner interpolative substep to obtain the echo data of an interpolation point. The aliasing determination substep is used for deciding whether the aliasing occurs on the neighbor point ultrasound echo data. If the aliasing occurs, firstly, the echo data revision substep is implemented, and then the neighbor point inner interpolative substep is implemented; if the aliasing does not occur, the echo data revision substep is omitted, the neighbor point inner interpolative substep is directly implanted. The method can weaken noise caused by aliasing in the colorultrasound imaging system. In addition, the calculated amount and the storage room spent by the interpolation algorism used by the method are all less. The invention also provides a device which usesthe method.

Abstract: In this paper, an extended projection temporal logic(EPTL), based on a primitive operator prj , is formalized. Further, as an executable subset of EPTL, an object-oriented MSVL is presented, which extends the temporal logic programming language MSVL to support object, class, aliasing, inheritance and overloading features. An example of modeling and simulating digital signal processing is given to illustrate how to use and execute the language.© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.