Super-Resolution Algorithm in Cumulative Virtual Blanking

Science.gov (United States)

Montillet, J. P.; Meng, X.; Roberts, G. W.; Woolfson, M. S.

2008-11-01

The proliferation of mobile devices and the emergence of wireless location-based services have generated consumer demand for precise location. In this paper, the MUSIC super-resolution algorithm is applied to time delay estimation for positioning purposes in cellular networks. The goal is to position a Mobile Station with UMTS technology. The problem of Base-Stations herability is solved using Cumulative Virtual Blanking. A simple simulator is presented using DS-SS signal. The results show that MUSIC algorithm improves the time delay estimation in both the cases whether or not Cumulative Virtual Blanking was carried out.

The Chorus Conflict and Loss of Separation Resolution Algorithms

Science.gov (United States)

Butler, Ricky W.; Hagen, George E.; Maddalon, Jeffrey M.

2013-01-01

The Chorus software is designed to investigate near-term, tactical conflict and loss of separation detection and resolution concepts for air traffic management. This software is currently being used in two different problem domains: en-route self- separation and sense and avoid for unmanned aircraft systems. This paper describes the core resolution algorithms that are part of Chorus. The combination of several features of the Chorus program distinguish this software from other approaches to conflict and loss of separation resolution. First, the program stores a history of state information over time which enables it to handle communication dropouts and take advantage of previous input data. Second, the underlying conflict algorithms find resolutions that solve the most urgent conflict, but also seek to prevent secondary conflicts with the other aircraft. Third, if the program is run on multiple aircraft, and the two aircraft maneuver at the same time, the result will be implicitly co-ordinated. This implicit coordination property is established by ensuring that a resolution produced by Chorus will comply with a mathematically-defined criteria whose correctness has been formally verified. Fourth, the program produces both instantaneous solutions and kinematic solutions, which are based on simple accel- eration models. Finally, the program provides resolutions for recovery from loss of separation. Different versions of this software are implemented as Java and C++ software programs, respectively.

The Effect of Swarming on a Voltage Potential-Based Conflict Resolution Algorithm

NARCIS (Netherlands)

Maas, J.B.; Sunil, E.; Ellerbroek, J.; Hoekstra, J.M.; Tra, M.A.P.

2016-01-01

Several conflict resolution algorithms for airborne self-separation rely on principles derived from the repulsive forces that exist between similarly charged particles. This research investigates whether the performance of the Modified Voltage Potential algorithm, which is based on this algorithm,

Experimental Performance of a Genetic Algorithm for Airborne Strategic Conflict Resolution

Science.gov (United States)

Karr, David A.; Vivona, Robert A.; Roscoe, David A.; DePascale, Stephen M.; Consiglio, Maria

2009-01-01

The Autonomous Operations Planner, a research prototype flight-deck decision support tool to enable airborne self-separation, uses a pattern-based genetic algorithm to resolve predicted conflicts between the ownship and traffic aircraft. Conflicts are resolved by modifying the active route within the ownship's flight management system according to a predefined set of maneuver pattern templates. The performance of this pattern-based genetic algorithm was evaluated in the context of batch-mode Monte Carlo simulations running over 3600 flight hours of autonomous aircraft in en-route airspace under conditions ranging from typical current traffic densities to several times that level. Encountering over 8900 conflicts during two simulation experiments, the genetic algorithm was able to resolve all but three conflicts, while maintaining a required time of arrival constraint for most aircraft. Actual elapsed running time for the algorithm was consistent with conflict resolution in real time. The paper presents details of the genetic algorithm's design, along with mathematical models of the algorithm's performance and observations regarding the effectiveness of using complimentary maneuver patterns when multiple resolutions by the same aircraft were required.

A Novel Method to Implement the Matrix Pencil Super Resolution Algorithm for Indoor Positioning

Directory of Open Access Journals (Sweden)

Tariq Jamil Saifullah Khanzada

2011-10-01

Full Text Available This article highlights the estimation of the results for the algorithms implemented in order to estimate the delays and distances for the indoor positioning system. The data sets for the transmitted and received signals are captured at a typical outdoor and indoor area. The estimation super resolution algorithms are applied. Different state of art and super resolution techniques based algorithms are applied to avail the optimal estimates of the delays and distances between the transmitted and received signals and a novel method for matrix pencil algorithm is devised. The algorithms perform variably at different scenarios of transmitted and received positions. Two scenarios are experienced, for the single antenna scenario the super resolution techniques like ESPRIT (Estimation of Signal Parameters via Rotational Invariance Technique and theMatrix Pencil algorithms give optimal performance compared to the conventional techniques. In two antenna scenario RootMUSIC and Matrix Pencil algorithm performed better than other algorithms for the distance estimation, however, the accuracy of all the algorithms is worst than the single antenna scenario. In all cases our devised Matrix Pencil algorithm achieved the best estimation results.

Comparative analysis of time efficiency and spatial resolution between different EIT reconstruction algorithms

International Nuclear Information System (INIS)

Kacarska, Marija; Loskovska, Suzana

2002-01-01

In this paper comparative analysis between different EIT algorithms is presented. Analysis is made for spatial and temporal resolution of obtained images by several different algorithms. Discussions consider spatial resolution dependent on data acquisition method, too. Obtained results show that conventional applied-current EIT is more powerful compared to induced-current EIT. (Author)

Generalized Nonlinear Chirp Scaling Algorithm for High-Resolution Highly Squint SAR Imaging.

Science.gov (United States)

Yi, Tianzhu; He, Zhihua; He, Feng; Dong, Zhen; Wu, Manqing

2017-11-07

This paper presents a modified approach for high-resolution, highly squint synthetic aperture radar (SAR) data processing. Several nonlinear chirp scaling (NLCS) algorithms have been proposed to solve the azimuth variance of the frequency modulation rates that are caused by the linear range walk correction (LRWC). However, the azimuth depth of focusing (ADOF) is not handled well by these algorithms. The generalized nonlinear chirp scaling (GNLCS) algorithm that is proposed in this paper uses the method of series reverse (MSR) to improve the ADOF and focusing precision. It also introduces a high order processing kernel to avoid the range block processing. Simulation results show that the GNLCS algorithm can enlarge the ADOF and focusing precision for high-resolution highly squint SAR data.

Generalized Nonlinear Chirp Scaling Algorithm for High-Resolution Highly Squint SAR Imaging

Directory of Open Access Journals (Sweden)

Tianzhu Yi

2017-11-01

Full Text Available This paper presents a modified approach for high-resolution, highly squint synthetic aperture radar (SAR data processing. Several nonlinear chirp scaling (NLCS algorithms have been proposed to solve the azimuth variance of the frequency modulation rates that are caused by the linear range walk correction (LRWC. However, the azimuth depth of focusing (ADOF is not handled well by these algorithms. The generalized nonlinear chirp scaling (GNLCS algorithm that is proposed in this paper uses the method of series reverse (MSR to improve the ADOF and focusing precision. It also introduces a high order processing kernel to avoid the range block processing. Simulation results show that the GNLCS algorithm can enlarge the ADOF and focusing precision for high-resolution highly squint SAR data.

Effects of ray profile modeling on resolution recovery in clinical CT

International Nuclear Information System (INIS)

Hofmann, Christian; Knaup, Michael; Kachelrieß, Marc

2014-01-01

be able to focus on comparing spatial resolution. The authors use two different simulation settings. Both are based on the geometry of a typical clinical CT system (0.7 mm detector element size at isocenter, 1024 projections per rotation). Setting one has an exaggerated source width of 5.0 mm. Setting two has a realistically small source width of 0.5 mm. The authors also investigate the transition from setting one to two. To quantify image quality, the authors analyze line profiles through the resolution patterns to define a contrast factor (CF) for contrast-resolution plots, and the authors compare the normalized cross-correlation (NCC) with respect to the ground truth of the circular resolution patterns. To independently analyze whether RM is of advantage, the authors implemented several iterative reconstruction algorithms: The statistical iterative reconstruction algorithm OSC, the ordered subsets simultaneous algebraic reconstruction technique (OSSART) and another statistical iterative reconstruction algorithm, denoted with ordered subsets maximum likelihood (OSML) algorithm. All algorithms were implemented both without RM (denoted as OSC, OSSART, and OSML) and with RM (denoted as OSC-RM, OSSART-RM, and OSML-RM). Results: For the unrealistic case of a 5.0 mm focal spot the CF can be improved by a factor of two due to RM: the 4.2 LP/cm bar pattern, which is the first bar pattern that cannot be resolved without RM, can be easily resolved with RM. For the realistic case of a 0.5 mm focus, all results show approximately the same CF. The NCC shows no significant dependency on RM when the source width is smaller than 2.0 mm (as in clinical CT). From 2.0 mm to 5.0 mm focal spot size increasing improvements can be observed with RM. Conclusions: Geometric RM in iterative reconstruction helps improving spatial resolution, if the ray cross-section is significantly larger than the ray sampling distance. In clinical CT, however, the ray is not much thicker than the distance

A Denotational Semantics for Communicating Unstructured Code

Directory of Open Access Journals (Sweden)

Nils Jähnig

2015-03-01

Full Text Available An important property of programming language semantics is that they should be compositional. However, unstructured low-level code contains goto-like commands making it hard to define a semantics that is compositional. In this paper, we follow the ideas of Saabas and Uustalu to structure low-level code. This gives us the possibility to define a compositional denotational semantics based on least fixed points to allow for the use of inductive verification methods. We capture the semantics of communication using finite traces similar to the denotations of CSP. In addition, we examine properties of this semantics and give an example that demonstrates reasoning about communication and jumps. With this semantics, we lay the foundations for a proof calculus that captures both, the semantics of unstructured low-level code and communication.

Super-resolution reconstruction of MR image with a novel residual learning network algorithm

Science.gov (United States)

Shi, Jun; Liu, Qingping; Wang, Chaofeng; Zhang, Qi; Ying, Shihui; Xu, Haoyu

2018-04-01

Spatial resolution is one of the key parameters of magnetic resonance imaging (MRI). The image super-resolution (SR) technique offers an alternative approach to improve the spatial resolution of MRI due to its simplicity. Convolutional neural networks (CNN)-based SR algorithms have achieved state-of-the-art performance, in which the global residual learning (GRL) strategy is now commonly used due to its effectiveness for learning image details for SR. However, the partial loss of image details usually happens in a very deep network due to the degradation problem. In this work, we propose a novel residual learning-based SR algorithm for MRI, which combines both multi-scale GRL and shallow network block-based local residual learning (LRL). The proposed LRL module works effectively in capturing high-frequency details by learning local residuals. One simulated MRI dataset and two real MRI datasets have been used to evaluate our algorithm. The experimental results show that the proposed SR algorithm achieves superior performance to all of the other compared CNN-based SR algorithms in this work.

Improving the resolution for Lamb wave testing via a smoothed Capon algorithm

Science.gov (United States)

Cao, Xuwei; Zeng, Liang; Lin, Jing; Hua, Jiadong

2018-04-01

Lamb wave testing is promising for damage detection and evaluation in large-area structures. The dispersion of Lamb waves is often unavoidable, restricting testing resolution and making the signal hard to interpret. A smoothed Capon algorithm is proposed in this paper to estimate the accurate path length of each wave packet. In the algorithm, frequency domain whitening is firstly used to obtain the transfer function in the bandwidth of the excitation pulse. Subsequently, wavenumber domain smoothing is employed to reduce the correlation between wave packets. Finally, the path lengths are determined by distance domain searching based on the Capon algorithm. Simulations are applied to optimize the number of smoothing times. Experiments are performed on an aluminum plate consisting of two simulated defects. The results demonstrate that spatial resolution is improved significantly by the proposed algorithm.

Low-Cost Super-Resolution Algorithms Implementation Over a HW/SW Video Compression Platform

Directory of Open Access Journals (Sweden)

Llopis Rafael Peset

2006-01-01

Full Text Available Two approaches are presented in this paper to improve the quality of digital images over the sensor resolution using super-resolution techniques: iterative super-resolution (ISR and noniterative super-resolution (NISR algorithms. The results show important improvements in the image quality, assuming that sufficient sample data and a reasonable amount of aliasing are available at the input images. These super-resolution algorithms have been implemented over a codesign video compression platform developed by Philips Research, performing minimal changes on the overall hardware architecture. In this way, a novel and feasible low-cost implementation has been obtained by using the resources encountered in a generic hybrid video encoder. Although a specific video codec platform has been used, the methodology presented in this paper is easily extendable to any other video encoder architectures. Finally a comparison in terms of memory, computational load, and image quality for both algorithms, as well as some general statements about the final impact of the sampling process on the quality of the super-resolved (SR image, are also presented.

Nuclear denotation: a topic for global public health concern

International Nuclear Information System (INIS)

Wiwanitkit, Viroj

2011-01-01

In mid of March 2011, a big Tsunami attacked Japan and caused serious destruction. In addition to the destroyed infrastructure, disruption of the nuclear plants occurred and this is the origin of the big problem of nuclear denotation which is of present concern. Nuclear denotation is an actually interesting new problem that affects a large group of world population. This situation is new and requires our attention in a global level. In this article, the author summarizes and discusses this important topic

A New Block Processing Algorithm of LLL for Fast High-dimension Ambiguity Resolution

Directory of Open Access Journals (Sweden)

LIU Wanke

2016-02-01

Full Text Available Due to high dimension and precision for the ambiguity vector under GNSS observations of multi-frequency and multi-system, a major problem to limit computational efficiency of ambiguity resolution is the longer reduction time when using conventional LLL algorithm. To address this problem, it is proposed a new block processing algorithm of LLL by analyzing the relationship between the reduction time and the dimensions and precision of ambiguity. The new algorithm reduces the reduction time to improve computational efficiency of ambiguity resolution, which is based on block processing ambiguity variance-covariance matrix that decreased the dimensions of single reduction matrix. It is validated that the new algorithm with two groups of measured data. The results show that the computing efficiency of the new algorithm increased by 65.2% and 60.2% respectively compared with that of LLL algorithm when choosing a reasonable number of blocks.

What's in a Name? Denotation, Connotation, and "A Boy Named Sue"

Science.gov (United States)

Lawton, Bessie

2011-01-01

Language choice--specifically word choice--is an important topic on a basic communication or public speaking course. One sub-topic under "Language" involves understanding the difference between denotation and connotation. Denotation refers to a word's definition, while connotation refers to the emotions associated with the word. Speakers need to…

A Turn-Projected State-Based Conflict Resolution Algorithm

Science.gov (United States)

Butler, Ricky W.; Lewis, Timothy A.

2013-01-01

State-based conflict detection and resolution (CD&R) algorithms detect conflicts and resolve them on the basis on current state information without the use of additional intent information from aircraft flight plans. Therefore, the prediction of the trajectory of aircraft is based solely upon the position and velocity vectors of the traffic aircraft. Most CD&R algorithms project the traffic state using only the current state vectors. However, the past state vectors can be used to make a better prediction of the future trajectory of the traffic aircraft. This paper explores the idea of using past state vectors to detect traffic turns and resolve conflicts caused by these turns using a non-linear projection of the traffic state. A new algorithm based on this idea is presented and validated using a fast-time simulator developed for this study.

Application of regularization technique in image super-resolution algorithm via sparse representation

Science.gov (United States)

Huang, De-tian; Huang, Wei-qin; Huang, Hui; Zheng, Li-xin

2017-11-01

To make use of the prior knowledge of the image more effectively and restore more details of the edges and structures, a novel sparse coding objective function is proposed by applying the principle of the non-local similarity and manifold learning on the basis of super-resolution algorithm via sparse representation. Firstly, the non-local similarity regularization term is constructed by using the similar image patches to preserve the edge information. Then, the manifold learning regularization term is constructed by utilizing the locally linear embedding approach to enhance the structural information. The experimental results validate that the proposed algorithm has a significant improvement compared with several super-resolution algorithms in terms of the subjective visual effect and objective evaluation indices.

10 CFR 1703.102 - Definitions; words denoting number, gender and tense.

Science.gov (United States)

2010-01-01

... 10 Energy 4 2010-01-01 2010-01-01 false Definitions; words denoting number, gender and tense. 1703... § 1703.102 Definitions; words denoting number, gender and tense. Agency record is a record in the possession and control of the Board that is associated with Board business. Agency records do not include...

18 CFR 1.102 - Words denoting number, gender and so forth.

Science.gov (United States)

2010-04-01

... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Words denoting number... Rules of Construction § 1.102 Words denoting number, gender and so forth. In determining the meaning of...) Words of one gender include the other gender. [Order 225, 47 FR 19022, May 3, 1982] ...

Comparison between beamforming and super resolution imaging algorithms for non-destructive evaluation

Energy Technology Data Exchange (ETDEWEB)

Fan, Chengguang [College of Mechatronic Engineering and Automation, National University of Defense Technology, Changsha 410073, PR China and Department of Mechanical Engineering, University of Bristol, Queen' s Building, University Walk, Bristol BS8 1TR (United Kingdom); Drinkwater, Bruce W. [Department of Mechanical Engineering, University of Bristol, Queen' s Building, University Walk, Bristol BS8 1TR (United Kingdom)

2014-02-18

In this paper the performance of total focusing method is compared with the widely used time-reversal MUSIC super resolution technique. The algorithms are tested with simulated and experimental ultrasonic array data, each containing different noise levels. The simulated time domain signals allow the effects of array geometry, frequency, scatterer location, scatterer size, scatterer separation and random noise to be carefully controlled. The performance of the imaging algorithms is evaluated in terms of resolution and sensitivity to random noise. It is shown that for the low noise situation, time-reversal MUSIC provides enhanced lateral resolution when compared to the total focusing method. However, for higher noise levels, the total focusing method shows robustness, whilst the performance of time-reversal MUSIC is significantly degraded.

Comparison between beamforming and super resolution imaging algorithms for non-destructive evaluation

International Nuclear Information System (INIS)

Fan, Chengguang; Drinkwater, Bruce W.

2014-01-01

In this paper the performance of total focusing method is compared with the widely used time-reversal MUSIC super resolution technique. The algorithms are tested with simulated and experimental ultrasonic array data, each containing different noise levels. The simulated time domain signals allow the effects of array geometry, frequency, scatterer location, scatterer size, scatterer separation and random noise to be carefully controlled. The performance of the imaging algorithms is evaluated in terms of resolution and sensitivity to random noise. It is shown that for the low noise situation, time-reversal MUSIC provides enhanced lateral resolution when compared to the total focusing method. However, for higher noise levels, the total focusing method shows robustness, whilst the performance of time-reversal MUSIC is significantly degraded

Computational performance of a projection and rescaling algorithm

OpenAIRE

Pena, Javier; Soheili, Negar

2018-01-01

This paper documents a computational implementation of a {\\em projection and rescaling algorithm} for finding most interior solutions to the pair of feasibility problems \\[ \\text{find} \\; x\\in L\\cap\\mathbb{R}^n_{+} \\;\\;\\;\\; \\text{ and } \\; \\;\\;\\;\\; \\text{find} \\; \\hat x\\in L^\\perp\\cap\\mathbb{R}^n_{+}, \\] where $L$ denotes a linear subspace in $\\mathbb{R}^n$ and $L^\\perp$ denotes its orthogonal complement. The projection and rescaling algorithm is a recently developed method that combines a {\\...

A Super-resolution Reconstruction Algorithm for Surveillance Video

Directory of Open Access Journals (Sweden)

Jian Shao

2017-01-01

Full Text Available Recent technological developments have resulted in surveillance video becoming a primary method of preserving public security. Many city crimes are observed in surveillance video. The most abundant evidence collected by the police is also acquired through surveillance video sources. Surveillance video footage offers very strong support for solving criminal cases, therefore, creating an effective policy, and applying useful methods to the retrieval of additional evidence is becoming increasingly important. However, surveillance video has had its failings, namely, video footage being captured in low resolution (LR and bad visual quality. In this paper, we discuss the characteristics of surveillance video and describe the manual feature registration – maximum a posteriori – projection onto convex sets to develop a super-resolution reconstruction method, which improves the quality of surveillance video. From this method, we can make optimal use of information contained in the LR video image, but we can also control the image edge clearly as well as the convergence of the algorithm. Finally, we make a suggestion on how to adjust the algorithm adaptability by analyzing the prior information of target image.

Denotative and connotative meanings of paintings

Directory of Open Access Journals (Sweden)

Vasić Sandra

2007-01-01

Full Text Available In this study the relationships between judgments of paintings denotative and connotative meanings was investigated. Denotative domain was defined as motif (represented object, e.g. portrait, landscape etc. and message (information carried by paintings, e.g. celebration of patriotism. Connotative domain was defined as subjective experience, i.e. affective or metaphoric impression produced by painting (e.g. feeling of pleasure, impression of dynamics, and so on. In preliminary study the list of 39 motifs was specified empirically. The four dimensions of pictorial message were taken from the previous study (Marković, 2006: Subjectivism, Ideology, Decoration and Constructivism vs. Realism. The four dimensions of paintings subjective experience were taken from the previous study as well (Radonjić and Marković, 2005: Regularity, Attraction, Arousal and Relaxation. In Experiment 1 subjects were asked to associate 39 motifs with 18 paintings. In Experiment 2 subjects were asked to judge 24 paintings on four dimensions of pictorial message. Results form Experiment 1 have shown that dimensions of paintings subjective experience were significantly correlated with only five motifs (e.g. everyday life was negatively correlated with Arousal, battle was negatively correlated with Relaxation, and so on. Results from Experiment 2 have shown that Subjectivism and Constructivism are negatively correlated with Regularity, and positively correlated with Arousal. Decoration is negatively correlated with Arousal and positively with Attraction and Relaxation.

Fast algorithm of adaptive Fourier series

Science.gov (United States)

Gao, You; Ku, Min; Qian, Tao

2018-05-01

Adaptive Fourier decomposition (AFD, precisely 1-D AFD or Core-AFD) was originated for the goal of positive frequency representations of signals. It achieved the goal and at the same time offered fast decompositions of signals. There then arose several types of AFDs. AFD merged with the greedy algorithm idea, and in particular, motivated the so-called pre-orthogonal greedy algorithm (Pre-OGA) that was proven to be the most efficient greedy algorithm. The cost of the advantages of the AFD type decompositions is, however, the high computational complexity due to the involvement of maximal selections of the dictionary parameters. The present paper offers one formulation of the 1-D AFD algorithm by building the FFT algorithm into it. Accordingly, the algorithm complexity is reduced, from the original $\\mathcal{O}(M N^2)$ to $\\mathcal{O}(M N\\log_2 N)$, where $N$ denotes the number of the discretization points on the unit circle and $M$ denotes the number of points in $[0,1)$. This greatly enhances the applicability of AFD. Experiments are carried out to show the high efficiency of the proposed algorithm.

Principle and Reconstruction Algorithm for Atomic-Resolution Holography

Science.gov (United States)

Matsushita, Tomohiro; Muro, Takayuki; Matsui, Fumihiko; Happo, Naohisa; Hosokawa, Shinya; Ohoyama, Kenji; Sato-Tomita, Ayana; Sasaki, Yuji C.; Hayashi, Kouichi

2018-06-01

Atomic-resolution holography makes it possible to obtain the three-dimensional (3D) structure around a target atomic site. Translational symmetry of the atomic arrangement of the sample is not necessary, and the 3D atomic image can be measured when the local structure of the target atomic site is oriented. Therefore, 3D local atomic structures such as dopants and adsorbates are observable. Here, the atomic-resolution holography comprising photoelectron holography, X-ray fluorescence holography, neutron holography, and their inverse modes are treated. Although the measurement methods are different, they can be handled with a unified theory. The algorithm for reconstructing 3D atomic images from holograms plays an important role. Although Fourier transform-based methods have been proposed, they require the multiple-energy holograms. In addition, they cannot be directly applied to photoelectron holography because of the phase shift problem. We have developed methods based on the fitting method for reconstructing from single-energy and photoelectron holograms. The developed methods are applicable to all types of atomic-resolution holography.

HWDA: A coherence recognition and resolution algorithm for hybrid web data aggregation

Science.gov (United States)

Guo, Shuhang; Wang, Jian; Wang, Tong

2017-09-01

Aiming at the object confliction recognition and resolution problem for hybrid distributed data stream aggregation, a distributed data stream object coherence solution technology is proposed. Firstly, the framework was defined for the object coherence conflict recognition and resolution, named HWDA. Secondly, an object coherence recognition technology was proposed based on formal language description logic and hierarchical dependency relationship between logic rules. Thirdly, a conflict traversal recognition algorithm was proposed based on the defined dependency graph. Next, the conflict resolution technology was prompted based on resolution pattern matching including the definition of the three types of conflict, conflict resolution matching pattern and arbitration resolution method. At last, the experiment use two kinds of web test data sets to validate the effect of application utilizing the conflict recognition and resolution technology of HWDA.

A novel algorithm of super-resolution image reconstruction based on multi-class dictionaries for natural scene

Science.gov (United States)

Wu, Wei; Zhao, Dewei; Zhang, Huan

2015-12-01

Super-resolution image reconstruction is an effective method to improve the image quality. It has important research significance in the field of image processing. However, the choice of the dictionary directly affects the efficiency of image reconstruction. A sparse representation theory is introduced into the problem of the nearest neighbor selection. Based on the sparse representation of super-resolution image reconstruction method, a super-resolution image reconstruction algorithm based on multi-class dictionary is analyzed. This method avoids the redundancy problem of only training a hyper complete dictionary, and makes the sub-dictionary more representatives, and then replaces the traditional Euclidean distance computing method to improve the quality of the whole image reconstruction. In addition, the ill-posed problem is introduced into non-local self-similarity regularization. Experimental results show that the algorithm is much better results than state-of-the-art algorithm in terms of both PSNR and visual perception.

Airport Traffic Conflict Detection and Resolution Algorithm Evaluation

Science.gov (United States)

Jones, Denise R.; Chartrand, Ryan C.; Wilson, Sara R.; Commo, Sean A.; Ballard, Kathryn M.; Otero, Sharon D.; Barker, Glover D.

2016-01-01

Two conflict detection and resolution (CD&R) algorithms for the terminal maneuvering area (TMA) were evaluated in a fast-time batch simulation study at the National Aeronautics and Space Administration (NASA) Langley Research Center. One CD&R algorithm, developed at NASA, was designed to enhance surface situation awareness and provide cockpit alerts of potential conflicts during runway, taxi, and low altitude air-to-air operations. The second algorithm, Enhanced Traffic Situation Awareness on the Airport Surface with Indications and Alerts (SURF IA), was designed to increase flight crew awareness of the runway environment and facilitate an appropriate and timely response to potential conflict situations. The purpose of the study was to evaluate the performance of the aircraft-based CD&R algorithms during various runway, taxiway, and low altitude scenarios, multiple levels of CD&R system equipage, and various levels of horizontal position accuracy. Algorithm performance was assessed through various metrics including the collision rate, nuisance and missed alert rate, and alert toggling rate. The data suggests that, in general, alert toggling, nuisance and missed alerts, and unnecessary maneuvering occurred more frequently as the position accuracy was reduced. Collision avoidance was more effective when all of the aircraft were equipped with CD&R and maneuvered to avoid a collision after an alert was issued. In order to reduce the number of unwanted (nuisance) alerts when taxiing across a runway, a buffer is needed between the hold line and the alerting zone so alerts are not generated when an aircraft is behind the hold line. All of the results support RTCA horizontal position accuracy requirements for performing a CD&R function to reduce the likelihood and severity of runway incursions and collisions.

Semantic motivation for the denotational identity of arguments in predication structures

Directory of Open Access Journals (Sweden)

Viara Maldjieva

2015-11-01

Full Text Available Semantic motivation for the denotational identity of arguments in predication structures This text is an attempt at a preliminary outline of the factors that motivate the denotational identity of argument content in the predication structure as well as the consequences of this identity for the shape of the sentence expression which is a realization of such a structure. The first question this analysis attempts to answer concerns the structure of predicative concepts that constitute the predication structure with arguments of the identical content? The second question the cursory analysis done attempts to answer concerns the manner, in which the identity existing on the semantic structure level is signaled on the surface, in the formal structure.

Comparison of 3D Maximum A Posteriori and Filtered Backprojection algorithms for high resolution animal imaging in microPET

International Nuclear Information System (INIS)

Chatziioannou, A.; Qi, J.; Moore, A.; Annala, A.; Nguyen, K.; Leahy, R.M.; Cherry, S.R.

2000-01-01

We have evaluated the performance of two three dimensional reconstruction algorithms with data acquired from microPET, a high resolution tomograph dedicated to small animal imaging. The first was a linear filtered-backprojection algorithm (FBP) with reprojection of the missing data and the second was a statistical maximum-aposteriori probability algorithm (MAP). The two algorithms were evaluated in terms of their resolution performance, both in phantoms and in vivo. Sixty independent realizations of a phantom simulating the brain of a baby monkey were acquired, each containing 3 million counts. Each of these realizations was reconstructed independently with both algorithms. The ensemble of the sixty reconstructed realizations was used to estimate the standard deviation as a measure of the noise for each reconstruction algorithm. More detail was recovered in the MAP reconstruction without an increase in noise relative to FBP. Studies in a simple cylindrical compartment phantom demonstrated improved recovery of known activity ratios with MAP. Finally in vivo studies also demonstrated a clear improvement in spatial resolution using the MAP algorithm. The quantitative accuracy of the MAP reconstruction was also evaluated by comparison with autoradiography and direct well counting of tissue samples and was shown to be superior

A new automated assign and analysing method for high-resolution rotationally resolved spectra using genetic algorithms

NARCIS (Netherlands)

Meerts, W.L.; Schmitt, M.

2006-01-01

This paper describes a numerical technique that has recently been developed to automatically assign and fit high-resolution spectra. The method makes use of genetic algorithms (GA). The current algorithm is compared with previously used analysing methods. The general features of the GA and its

Denotational semantics of recursive types in synthetic guarded domain theory

DEFF Research Database (Denmark)

Møgelberg, Rasmus Ejlers; Paviotti, Marco

2016-01-01

typed lambda calculus with fixed points). This model was intensional in that it could distinguish between computations computing the same result using a different number of fixed point unfoldings. In this work we show how also programming languages with recursive types can be given denotational...

Convergence and resolution recovery of block-iterative EM algorithms modeling 3D detector response in SPECT

International Nuclear Information System (INIS)

Lalush, D.S.; Tsui, B.M.W.; Karimi, S.S.

1996-01-01

We evaluate fast reconstruction algorithms including ordered subsets-EM (OS-EM) and Rescaled Block Iterative EM (RBI-EM) in fully 3D SPECT applications on the basis of their convergence and resolution recovery properties as iterations proceed. Using a 3D computer-simulated phantom consisting of 3D Gaussian objects, we simulated projection data that includes only the effects of sampling and detector response of a parallel-hole collimator. Reconstructions were performed using each of the three algorithms (ML-EM, OS-EM, and RBI-EM) modeling the 3D detector response in the projection function. Resolution recovery was evaluated by fitting Gaussians to each of the four objects in the iterated image estimates at selected intervals. Results show that OS-EM and RBI-EM behave identically in this case; their resolution recovery results are virtually indistinguishable. Their resolution behavior appears to be very similar to that of ML-EM, but accelerated by a factor of twenty. For all three algorithms, smaller objects take more iterations to converge. Next, we consider the effect noise has on convergence. For both noise-free and noisy data, we evaluate the log likelihood function at each subiteration of OS-EM and RBI-EM, and at each iteration of ML-EM. With noisy data, both OS-EM and RBI-EM give results for which the log-likelihood function oscillates. Especially for 180-degree acquisitions, RBI-EM oscillates less than OS-EM. Both OS-EM and RBI-EM appear to converge to solutions, but not to the ML solution. We conclude that both OS-EM and RBI-EM can be effective algorithms for fully 3D SPECT reconstruction. Both recover resolution similarly to ML-EM, only more quickly

On 0-Complete Partial Metric Spaces and Quantitative Fixed Point Techniques in Denotational Semantics

Directory of Open Access Journals (Sweden)

N. Shahzad

2013-01-01

Full Text Available In 1994, Matthews introduced the notion of partial metric space with the aim of providing a quantitative mathematical model suitable for program verification. Concretely, Matthews proved a partial metric version of the celebrated Banach fixed point theorem which has become an appropriate quantitative fixed point technique to capture the meaning of recursive denotational specifications in programming languages. In this paper we show that a few assumptions in statement of Matthews fixed point theorem can be relaxed in order to provide a quantitative fixed point technique useful to analyze the meaning of the aforementioned recursive denotational specifications in programming languages. In particular, we prove a new fixed point theorem for self-mappings between partial metric spaces in which the completeness has been replaced by 0-completeness and the contractive condition has been weakened in such a way that the new one best fits the requirements of practical problems in denotational semantics. Moreover, we provide examples that show that the hypothesis in the statement of our new result cannot be weakened. Finally, we show the potential applicability of the developed theory by means of analyzing a few concrete recursive denotational specifications, some of them admitting a unique meaning and others supporting multiple ones.

Equalization Algorithm for Distributed Energy Storage Systems in Islanded AC Microgrids

DEFF Research Database (Denmark)

Aldana, Nelson Leonardo Diaz; Hernández, Adriana Carolina Luna; Quintero, Juan Carlos Vasquez

2015-01-01

This paper presents a centralized strategy for equalizing the state of charge of distributed energy storage systems in an islanded ac microgrid. The strategy is based on a simple algorithm denoted as equalization algorithm, which modifies the charge or discharge ratio on the time, for distributed...

Pyramidal Watershed Segmentation Algorithm for High-Resolution Remote Sensing Images Using Discrete Wavelet Transforms

Directory of Open Access Journals (Sweden)

K. Parvathi

2009-01-01

Full Text Available The watershed transformation is a useful morphological segmentation tool for a variety of grey-scale images. However, over segmentation and under segmentation have become the key problems for the conventional algorithm. In this paper, an efficient segmentation method for high-resolution remote sensing image analysis is presented. Wavelet analysis is one of the most popular techniques that can be used to detect local intensity variation and hence the wavelet transformation is used to analyze the image. Wavelet transform is applied to the image, producing detail (horizontal, vertical, and diagonal and Approximation coefficients. The image gradient with selective regional minima is estimated with the grey-scale morphology for the Approximation image at a suitable resolution, and then the watershed is applied to the gradient image to avoid over segmentation. The segmented image is projected up to high resolutions using the inverse wavelet transform. The watershed segmentation is applied to small subset size image, demanding less computational time. We have applied our new approach to analyze remote sensing images. The algorithm was implemented in MATLAB. Experimental results demonstrated the method to be effective.

Algorithms for worst-case tolerance optimization

DEFF Research Database (Denmark)

Schjær-Jacobsen, Hans; Madsen, Kaj

1979-01-01

New algorithms are presented for the solution of optimum tolerance assignment problems. The problems considered are defined mathematically as a worst-case problem (WCP), a fixed tolerance problem (FTP), and a variable tolerance problem (VTP). The basic optimization problem without tolerances...... is denoted the zero tolerance problem (ZTP). For solution of the WCP we suggest application of interval arithmetic and also alternative methods. For solution of the FTP an algorithm is suggested which is conceptually similar to algorithms previously developed by the authors for the ZTP. Finally, the VTP...... is solved by a double-iterative algorithm in which the inner iteration is performed by the FTP- algorithm. The application of the algorithm is demonstrated by means of relatively simple numerical examples. Basic properties, such as convergence properties, are displayed based on the examples....

A research of road centerline extraction algorithm from high resolution remote sensing images

Science.gov (United States)

Zhang, Yushan; Xu, Tingfa

2017-09-01

Satellite remote sensing technology has become one of the most effective methods for land surface monitoring in recent years, due to its advantages such as short period, large scale and rich information. Meanwhile, road extraction is an important field in the applications of high resolution remote sensing images. An intelligent and automatic road extraction algorithm with high precision has great significance for transportation, road network updating and urban planning. The fuzzy c-means (FCM) clustering segmentation algorithms have been used in road extraction, but the traditional algorithms did not consider spatial information. An improved fuzzy C-means clustering algorithm combined with spatial information (SFCM) is proposed in this paper, which is proved to be effective for noisy image segmentation. Firstly, the image is segmented using the SFCM. Secondly, the segmentation result is processed by mathematical morphology to remover the joint region. Thirdly, the road centerlines are extracted by morphology thinning and burr trimming. The average integrity of the centerline extraction algorithm is 97.98%, the average accuracy is 95.36% and the average quality is 93.59%. Experimental results show that the proposed method in this paper is effective for road centerline extraction.

Improving angular resolution with Scan-MUSIC algorithm for real complex targets using 35-GHz millimeter-wave radar

Science.gov (United States)

Ly, Canh

2004-08-01

Scan-MUSIC algorithm, developed by the U.S. Army Research Laboratory (ARL), improves angular resolution for target detection with the use of a single rotatable radar scanning the angular region of interest. This algorithm has been adapted and extended from the MUSIC algorithm that has been used for a linear sensor array. Previously, it was shown that the SMUSIC algorithm and a Millimeter Wave radar can be used to resolve two closely spaced point targets that exhibited constructive interference, but not for the targets that exhibited destructive interference. Therefore, there were some limitations of the algorithm for the point targets. In this paper, the SMUSIC algorithm is applied to a problem of resolving real complex scatterer-type targets, which is more useful and of greater practical interest, particular for the future Army radar system. The paper presents results of the angular resolution of the targets, an M60 tank and an M113 Armored Personnel Carrier (APC), that are within the mainlobe of a Κα-band radar antenna. In particular, we applied the algorithm to resolve centroids of the targets that were placed within the beamwidth of the antenna. The collected coherent data using the stepped-frequency radar were compute magnitudely for the SMUSIC calculation. Even though there were significantly different signal returns for different orientations and offsets of the two targets, we resolved those two target centroids when they were as close as about 1/3 of the antenna beamwidth.

High-resolution studies of the structure of the solar atmosphere using a new imaging algorithm

Science.gov (United States)

Karovska, Margarita; Habbal, Shadia Rifai

1991-01-01

The results of the application of a new image restoration algorithm developed by Ayers and Dainty (1988) to the multiwavelength EUV/Skylab observations of the solar atmosphere are presented. The application of the algorithm makes it possible to reach a resolution better than 5 arcsec, and thus study the structure of the quiet sun on that spatial scale. The results show evidence for discrete looplike structures in the network boundary, 5-10 arcsec in size, at temperatures of 100,000 K.

A simple algorithm for computing positively weighted straight skeletons of monotone polygons☆

Science.gov (United States)

Biedl, Therese; Held, Martin; Huber, Stefan; Kaaser, Dominik; Palfrader, Peter

2015-01-01

We study the characteristics of straight skeletons of monotone polygonal chains and use them to devise an algorithm for computing positively weighted straight skeletons of monotone polygons. Our algorithm runs in O(nlog⁡n) time and O(n) space, where n denotes the number of vertices of the polygon. PMID:25648376

A simple algorithm for computing positively weighted straight skeletons of monotone polygons.

Science.gov (United States)

Biedl, Therese; Held, Martin; Huber, Stefan; Kaaser, Dominik; Palfrader, Peter

2015-02-01

We study the characteristics of straight skeletons of monotone polygonal chains and use them to devise an algorithm for computing positively weighted straight skeletons of monotone polygons. Our algorithm runs in [Formula: see text] time and [Formula: see text] space, where n denotes the number of vertices of the polygon.

Action Algebras and Model Algebras in Denotational Semantics

Science.gov (United States)

Guedes, Luiz Carlos Castro; Haeusler, Edward Hermann

This article describes some results concerning the conceptual separation of model dependent and language inherent aspects in a denotational semantics of a programming language. Before going into the technical explanation, the authors wish to relate a story that illustrates how correctly and precisely posed questions can influence the direction of research. By means of his questions, Professor Mosses aided the PhD research of one of the authors of this article and taught the other, who at the time was a novice supervisor, the real meaning of careful PhD supervision. The student’s research had been partially developed towards the implementation of programming languages through denotational semantics specification, and the student had developed a prototype [12] that compared relatively well to some industrial compilers of the PASCAL language. During a visit to the BRICS lab in Aarhus, the student’s supervisor gave Professor Mosses a draft of an article describing the prototype and its implementation experiments. The next day, Professor Mosses asked the supervisor, “Why is the generated code so efficient when compared to that generated by an industrial compiler?” and “You claim that the efficiency is simply a consequence of the Object- Orientation mechanisms used by the prototype programming language (C++); this should be better investigated. Pay more attention to the class of programs that might have this good comparison profile.” As a result of these aptly chosen questions and comments, the student and supervisor made great strides in the subsequent research; the advice provided by Professor Mosses made them perceive that the code generated for certain semantic domains was efficient because it mapped to the “right aspect” of the language semantics. (Certain functional types, used to represent mappings such as Stores and Environments, were pushed to the level of the object language (as in gcc). This had the side-effect of generating code for arrays in

Array diagnostics, spatial resolution, and filtering of undesired radiation with the 3D reconstruction algorithm

DEFF Research Database (Denmark)

Cappellin, C.; Pivnenko, Sergey; Jørgensen, E.

2013-01-01

This paper focuses on three important features of the 3D reconstruction algorithm of DIATOOL: the identification of array elements improper functioning and failure, the obtainable spatial resolution of the reconstructed fields and currents, and the filtering of undesired radiation and scattering...

A practical algorithm for the retrieval of floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar imagery

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Byongjun Hwang

2017-07-01

Full Text Available In this study, we present an algorithm for summer sea ice conditions that semi-automatically produces the floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar data. Currently, floe size distribution data from satellite images are very rare in the literature, mainly due to the lack of a reliable algorithm to produce such data. Here, we developed the algorithm by combining various image analysis methods, including Kernel Graph Cuts, distance transformation and watershed transformation, and a rule-based boundary revalidation. The developed algorithm has been validated against the ground truth that was extracted manually with the aid of 1-m resolution visible satellite data. Comprehensive validation analysis has shown both perspectives and limitations. The algorithm tends to fail to detect small floes (mostly less than 100 m in mean caliper diameter compared to ground truth, which is mainly due to limitations in water-ice segmentation. Some variability in the power law exponent of floe size distribution is observed due to the effects of control parameters in the process of de-noising, Kernel Graph Cuts segmentation, thresholds for boundary revalidation and image resolution. Nonetheless, the algorithm, for floes larger than 100 m, has shown a reasonable agreement with ground truth under various selections of these control parameters. Considering that the coverage and spatial resolution of satellite Synthetic Aperture Radar data have increased significantly in recent years, the developed algorithm opens a new possibility to produce large volumes of floe size distribution data, which is essential for improving our understanding and prediction of the Arctic sea ice cover

Analysis and Application of High Resolution Numerical Perturbation Algorithm for Convective-Diffusion Equation

International Nuclear Information System (INIS)

Gao Zhi; Shen Yi-Qing

2012-01-01

The high resolution numerical perturbation (NP) algorithm is analyzed and tested using various convective-diffusion equations. The NP algorithm is constructed by splitting the second order central difference schemes of both convective and diffusion terms of the convective-diffusion equation into upstream and downstream parts, then the perturbation reconstruction functions of the convective coefficient are determined using the power-series of grid interval and eliminating the truncated errors of the modified differential equation. The important nature, i.e. the upwind dominance nature, which is the basis to ensuring that the NP schemes are stable and essentially oscillation free, is firstly presented and verified. Various numerical cases show that the NP schemes are efficient, robust, and more accurate than the original second order central scheme

Enhanced spatial resolution in fluorescence molecular tomography using restarted L1-regularized nonlinear conjugate gradient algorithm.

Science.gov (United States)

Shi, Junwei; Liu, Fei; Zhang, Guanglei; Luo, Jianwen; Bai, Jing

2014-04-01

Owing to the high degree of scattering of light through tissues, the ill-posedness of fluorescence molecular tomography (FMT) inverse problem causes relatively low spatial resolution in the reconstruction results. Unlike L2 regularization, L1 regularization can preserve the details and reduce the noise effectively. Reconstruction is obtained through a restarted L1 regularization-based nonlinear conjugate gradient (re-L1-NCG) algorithm, which has been proven to be able to increase the computational speed with low memory consumption. The algorithm consists of inner and outer iterations. In the inner iteration, L1-NCG is used to obtain the L1-regularized results. In the outer iteration, the restarted strategy is used to increase the convergence speed of L1-NCG. To demonstrate the performance of re-L1-NCG in terms of spatial resolution, simulation and physical phantom studies with fluorescent targets located with different edge-to-edge distances were carried out. The reconstruction results show that the re-L1-NCG algorithm has the ability to resolve targets with an edge-to-edge distance of 0.1 cm at a depth of 1.5 cm, which is a significant improvement for FMT.

Super resolution reconstruction of μ-CT image of rock sample using neighbour embedding algorithm

Science.gov (United States)

Wang, Yuzhu; Rahman, Sheik S.; Arns, Christoph H.

2018-03-01

X-ray computed tomography (μ-CT) is considered to be the most effective way to obtain the inner structure of rock sample without destructions. However, its limited resolution hampers its ability to probe sub-micro structures which is critical for flow transportation of rock sample. In this study, we propose an innovative methodology to improve the resolution of μ-CT image using neighbour embedding algorithm where low frequency information is provided by μ-CT image itself while high frequency information is supplemented by high resolution scanning electron microscopy (SEM) image. In order to obtain prior for reconstruction, a large number of image patch pairs contain high- and low- image patches are extracted from the Gaussian image pyramid generated by SEM image. These image patch pairs contain abundant information about tomographic evolution of local porous structures under different resolution spaces. Relying on the assumption of self-similarity of porous structure, this prior information can be used to supervise the reconstruction of high resolution μ-CT image effectively. The experimental results show that the proposed method is able to achieve the state-of-the-art performance.

Improved Wallis Dodging Algorithm for Large-Scale Super-Resolution Reconstruction Remote Sensing Images

Directory of Open Access Journals (Sweden)

Chong Fan

2017-03-01

Full Text Available A sub-block algorithm is usually applied in the super-resolution (SR reconstruction of images because of limitations in computer memory. However, the sub-block SR images can hardly achieve a seamless image mosaicking because of the uneven distribution of brightness and contrast among these sub-blocks. An effectively improved weighted Wallis dodging algorithm is proposed, aiming at the characteristic that SR reconstructed images are gray images with the same size and overlapping region. This algorithm can achieve consistency of image brightness and contrast. Meanwhile, a weighted adjustment sequence is presented to avoid the spatial propagation and accumulation of errors and the loss of image information caused by excessive computation. A seam line elimination method can share the partial dislocation in the seam line to the entire overlapping region with a smooth transition effect. Subsequently, the improved method is employed to remove the uneven illumination for 900 SR reconstructed images of ZY-3. Then, the overlapping image mosaic method is adopted to accomplish a seamless image mosaic based on the optimal seam line.

SURF IA Conflict Detection and Resolution Algorithm Evaluation

Science.gov (United States)

Jones, Denise R.; Chartrand, Ryan C.; Wilson, Sara R.; Commo, Sean A.; Barker, Glover D.

2012-01-01

The Enhanced Traffic Situational Awareness on the Airport Surface with Indications and Alerts (SURF IA) algorithm was evaluated in a fast-time batch simulation study at the National Aeronautics and Space Administration (NASA) Langley Research Center. SURF IA is designed to increase flight crew situation awareness of the runway environment and facilitate an appropriate and timely response to potential conflict situations. The purpose of the study was to evaluate the performance of the SURF IA algorithm under various runway scenarios, multiple levels of conflict detection and resolution (CD&R) system equipage, and various levels of horizontal position accuracy. This paper gives an overview of the SURF IA concept, simulation study, and results. Runway incursions are a serious aviation safety hazard. As such, the FAA is committed to reducing the severity, number, and rate of runway incursions by implementing a combination of guidance, education, outreach, training, technology, infrastructure, and risk identification and mitigation initiatives [1]. Progress has been made in reducing the number of serious incursions - from a high of 67 in Fiscal Year (FY) 2000 to 6 in FY2010. However, the rate of all incursions has risen steadily over recent years - from a rate of 12.3 incursions per million operations in FY2005 to a rate of 18.9 incursions per million operations in FY2010 [1, 2]. The National Transportation Safety Board (NTSB) also considers runway incursions to be a serious aviation safety hazard, listing runway incursion prevention as one of their most wanted transportation safety improvements [3]. The NTSB recommends that immediate warning of probable collisions/incursions be given directly to flight crews in the cockpit [4].

Enhanced temporal resolution at cardiac CT with a novel CT image reconstruction algorithm: Initial patient experience

Energy Technology Data Exchange (ETDEWEB)

Apfaltrer, Paul, E-mail: paul.apfaltrer@medma.uni-heidelberg.de [Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, PO Box 250322, 169 Ashley Avenue, Charleston, SC 29425 (United States); Institute of Clinical Radiology and Nuclear Medicine, Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, D-68167 Mannheim (Germany); Schoendube, Harald, E-mail: harald.schoendube@siemens.com [Siemens Healthcare, CT Division, Forchheim Siemens, Siemensstr. 1, 91301 Forchheim (Germany); Schoepf, U. Joseph, E-mail: schoepf@musc.edu [Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, PO Box 250322, 169 Ashley Avenue, Charleston, SC 29425 (United States); Allmendinger, Thomas, E-mail: thomas.allmendinger@siemens.com [Siemens Healthcare, CT Division, Forchheim Siemens, Siemensstr. 1, 91301 Forchheim (Germany); Tricarico, Francesco, E-mail: francescotricarico82@gmail.com [Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, PO Box 250322, 169 Ashley Avenue, Charleston, SC 29425 (United States); Department of Bioimaging and Radiological Sciences, Catholic University of the Sacred Heart, “A. Gemelli” Hospital, Largo A. Gemelli 8, Rome (Italy); Schindler, Andreas, E-mail: andreas.schindler@campus.lmu.de [Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, PO Box 250322, 169 Ashley Avenue, Charleston, SC 29425 (United States); Vogt, Sebastian, E-mail: sebastian.vogt@siemens.com [Siemens Healthcare, CT Division, Forchheim Siemens, Siemensstr. 1, 91301 Forchheim (Germany); Sunnegårdh, Johan, E-mail: johan.sunnegardh@siemens.com [Siemens Healthcare, CT Division, Forchheim Siemens, Siemensstr. 1, 91301 Forchheim (Germany); and others

2013-02-15

Objective: To evaluate the effect of a temporal resolution improvement method (TRIM) for cardiac CT on diagnostic image quality for coronary artery assessment. Materials and methods: The TRIM-algorithm employs an iterative approach to reconstruct images from less than 180° of projections and uses a histogram constraint to prevent the occurrence of limited-angle artifacts. This algorithm was applied in 11 obese patients (7 men, 67.2 ± 9.8 years) who had undergone second generation dual-source cardiac CT with 120 kV, 175–426 mAs, and 500 ms gantry rotation. All data were reconstructed with a temporal resolution of 250 ms using traditional filtered-back projection (FBP) and of 200 ms using the TRIM-algorithm. Contrast attenuation and contrast-to-noise-ratio (CNR) were measured in the ascending aorta. The presence and severity of coronary motion artifacts was rated on a 4-point Likert scale. Results: All scans were considered of diagnostic quality. Mean BMI was 36 ± 3.6 kg/m{sup 2}. Average heart rate was 60 ± 9 bpm. Mean effective dose was 13.5 ± 4.6 mSv. When comparing FBP- and TRIM reconstructed series, the attenuation within the ascending aorta (392 ± 70.7 vs. 396.8 ± 70.1 HU, p > 0.05) and CNR (13.2 ± 3.2 vs. 11.7 ± 3.1, p > 0.05) were not significantly different. A total of 110 coronary segments were evaluated. All studies were deemed diagnostic; however, there was a significant (p < 0.05) difference in the severity score distribution of coronary motion artifacts between FBP (median = 2.5) and TRIM (median = 2.0) reconstructions. Conclusion: The algorithm evaluated here delivers diagnostic imaging quality of the coronary arteries despite 500 ms gantry rotation. Possible applications include improvement of cardiac imaging on slower gantry rotation systems or mitigation of the trade-off between temporal resolution and CNR in obese patients.

High-Resolution Sonars: What Resolution Do We Need for Target Recognition?

Directory of Open Access Journals (Sweden)

Pailhas Yan

2010-01-01

Full Text Available Target recognition in sonar imagery has long been an active research area in the maritime domain, especially in the mine-counter measure context. Recently it has received even more attention as new sensors with increased resolution have been developed; new threats to critical maritime assets and a new paradigm for target recognition based on autonomous platforms have emerged. With the recent introduction of Synthetic Aperture Sonar systems and high-frequency sonars, sonar resolution has dramatically increased and noise levels decreased. Sonar images are distance images but at high resolution they tend to appear visually as optical images. Traditionally algorithms have been developed specifically for imaging sonars because of their limited resolution and high noise levels. With high-resolution sonars, algorithms developed in the image processing field for natural images become applicable. However, the lack of large datasets has hampered the development of such algorithms. Here we present a fast and realistic sonar simulator enabling development and evaluation of such algorithms.We develop a classifier and then analyse its performances using our simulated synthetic sonar images. Finally, we discuss sensor resolution requirements to achieve effective classification of various targets and demonstrate that with high resolution sonars target highlight analysis is the key for target recognition.

Assimilation of low-level wind in a high-resolution mesoscale model using the back and forth nudging algorithm

Directory of Open Access Journals (Sweden)

Jean-François Mahfouf

2012-06-01

Full Text Available The performance of a new data assimilation algorithm called back and forth nudging (BFN is evaluated using a high-resolution numerical mesoscale model and simulated wind observations in the boundary layer. This new algorithm, of interest for the assimilation of high-frequency observations provided by ground-based active remote-sensing instruments, is straightforward to implement in a realistic atmospheric model. The convergence towards a steady-state profile can be achieved after five iterations of the BFN algorithm, and the algorithm provides an improved solution with respect to direct nudging. It is shown that the contribution of the nudging term does not dominate over other model physical and dynamical tendencies. Moreover, by running backward integrations with an adiabatic version of the model, the nudging coefficients do not need to be increased in order to stabilise the numerical equations. The ability of BFN to produce model changes upstream from the observations, in a similar way to 4-D-Var assimilation systems, is demonstrated. The capacity of the model to adjust to rapid changes in wind direction with the BFN is a first encouraging step, for example, to improve the detection and prediction of low-level wind shear phenomena through high-resolution mesoscale modelling over airports.

Improvement of the temporal resolution of cardiac CT reconstruction algorithms using an optimized filtering step

International Nuclear Information System (INIS)

Roux, S.; Desbat, L.; Koenig, A.; Grangeat, P.

2005-01-01

In this paper we study a property of the filtering step of multi-cycle reconstruction algorithm used in the field of cardiac CT. We show that the common filtering step procedure is not optimal in the case of divergent geometry and decrease slightly the temporal resolution. We propose to use the filtering procedure related to the work of Noo at al ( F.Noo, M. Defrise, R. Clakdoyle, and H. Kudo. Image reconstruction from fan-beam projections on less than a short-scan. Phys. Med.Biol., 47:2525-2546, July 2002)and show that this alternative allows to reach the optimal temporal resolution with the same computational effort. (N.C.)

Pascal Semantics by a Combination of Denotational Semantics and High-level Petri Nets

DEFF Research Database (Denmark)

Jensen, Kurt; Schmidt, Erik Meineche

1986-01-01

This paper describes the formal semantics of a subset of PASCAL, by means of a semantic model based on a combination of denotational semantics and high-level Petri nets. It is our intention that the paper can be used as part of the written material for an introductory course in computer science....

MO-FG-204-05: Evaluation of a Novel Algorithm for Improved 4DCT Resolution

Energy Technology Data Exchange (ETDEWEB)

Glide-Hurst, C; Briceno, J; Chetty, I. J. [Henry Ford Health System, Detroit, MI (United States); Klahr, P [Philips Healthcare, Highland Heights, OH (United States)

2015-06-15

Purpose: Accurate tumor motion characterization is critical for increasing the therapeutic ratio of radiation therapy. To accommodate the divergent fan-beam geometry of the scanner, the current 4D-CT algorithm utilizes a larger temporal window to ensure that pixel values are valid throughout the entire FOV. To minimize the impact on temporal resolution, a cos{sup 2} weighting is employed. We propose a novel exponential weighting (“exponential”) 4DCT reconstruction algorithm that has a sharper slope and provides a more optimal temporal resolution. Methods: A respiratory motion platform translated a lung-mimicking Styrofoam slab with several high and low-contrast inserts 2 cm in the superior-inferior direction. Breathing rates (10–15 bpm) and couch pitch (0.06–0.1 A.U.) were varied to assess interplay between parameters. Multi-slice helical 4DCTs were acquired with 0.5 sec gantry rotation and data were reconstructed with cos{sup 2} and exponential weighting. Mean and standard deviation were calculated via region of interest analysis. Intensity profiles evaluated object boundaries. Retrospective raw data reconstructions were performed for both 4DCT algorithms for 3 liver and lung cancer patients. Image quality (temporal blurring/sharpness) and subtraction images were compared between reconstructions. Results: In the phantom, profile analysis revealed that sharper boundaries were obtained with exponential reconstructions at transitioning breathing phases (i.e. mid-inhale or mid-exhale). Reductions in full-width half maximum were ∼1 mm in the superior-inferior direction and appreciable sharpness could be observed in difference maps. This reduction also yielded a slight reduction in target volume between reconstruction algorithms. For patient cases, coronal views showed less blurring at object boundaries and local intensity differences near the tumor and diaphragm with exponential weighted reconstruction. Conclusion: Exponential weighted 4DCT offers potential

Assessment of Atmospheric Algorithms to Retrieve Vegetation in Natural Protected Areas Using Multispectral High Resolution Imagery

Directory of Open Access Journals (Sweden)

Javier Marcello

2016-09-01

Full Text Available The precise mapping of vegetation covers in semi-arid areas is a complex task as this type of environment consists of sparse vegetation mainly composed of small shrubs. The launch of high resolution satellites, with additional spectral bands and the ability to alter the viewing angle, offers a useful technology to focus on this objective. In this context, atmospheric correction is a fundamental step in the pre-processing of such remote sensing imagery and, consequently, different algorithms have been developed for this purpose over the years. They are commonly categorized as imaged-based methods as well as in more advanced physical models based on the radiative transfer theory. Despite the relevance of this topic, a few comparative studies covering several methods have been carried out using high resolution data or which are specifically applied to vegetation covers. In this work, the performance of five representative atmospheric correction algorithms (DOS, QUAC, FLAASH, ATCOR and 6S has been assessed, using high resolution Worldview-2 imagery and field spectroradiometer data collected simultaneously, with the goal of identifying the most appropriate techniques. The study also included a detailed analysis of the parameterization influence on the final results of the correction, the aerosol model and its optical thickness being important parameters to be properly adjusted. The effects of corrections were studied in vegetation and soil sites belonging to different protected semi-arid ecosystems (high mountain and coastal areas. In summary, the superior performance of model-based algorithms, 6S in particular, has been demonstrated, achieving reflectance estimations very close to the in-situ measurements (RMSE of between 2% and 3%. Finally, an example of the importance of the atmospheric correction in the vegetation estimation in these natural areas is presented, allowing the robust mapping of species and the analysis of multitemporal variations

Resolution Enhancement of Multilook Imagery

Energy Technology Data Exchange (ETDEWEB)

Galbraith, Amy E. [Univ. of Arizona, Tucson, AZ (United States)

2004-07-01

This dissertation studies the feasibility of enhancing the spatial resolution of multi-look remotely-sensed imagery using an iterative resolution enhancement algorithm known as Projection Onto Convex Sets (POCS). A multi-angle satellite image modeling tool is implemented, and simulated multi-look imagery is formed to test the resolution enhancement algorithm. Experiments are done to determine the optimal con guration and number of multi-angle low-resolution images needed for a quantitative improvement in the spatial resolution of the high-resolution estimate. The important topic of aliasing is examined in the context of the POCS resolution enhancement algorithm performance. In addition, the extension of the method to multispectral sensor images is discussed and an example is shown using multispectral confocal fluorescence imaging microscope data. Finally, the remote sensing issues of atmospheric path radiance and directional reflectance variations are explored to determine their effect on the resolution enhancement performance.

DMPDS: A Fast Motion Estimation Algorithm Targeting High Resolution Videos and Its FPGA Implementation

Directory of Open Access Journals (Sweden)

Gustavo Sanchez

2012-01-01

Full Text Available This paper presents a new fast motion estimation (ME algorithm targeting high resolution digital videos and its efficient hardware architecture design. The new Dynamic Multipoint Diamond Search (DMPDS algorithm is a fast algorithm which increases the ME quality when compared with other fast ME algorithms. The DMPDS achieves a better digital video quality reducing the occurrence of local minima falls, especially in high definition videos. The quality results show that the DMPDS is able to reach an average PSNR gain of 1.85 dB when compared with the well-known Diamond Search (DS algorithm. When compared to the optimum results generated by the Full Search (FS algorithm the DMPDS shows a lose of only 1.03 dB in the PSNR. On the other hand, the DMPDS reached a complexity reduction higher than 45 times when compared to FS. The quality gains related to DS caused an expected increase in the DMPDS complexity which uses 6.4-times more calculations than DS. The DMPDS architecture was designed focused on high performance and low cost, targeting to process Quad Full High Definition (QFHD videos in real time (30 frames per second. The architecture was described in VHDL and synthesized to Altera Stratix 4 and Xilinx Virtex 5 FPGAs. The synthesis results show that the architecture is able to achieve processing rates higher than 53 QFHD fps, reaching the real-time requirements. The DMPDS architecture achieved the highest processing rate when compared to related works in the literature. This high processing rate was obtained designing an architecture with a high operation frequency and low numbers of cycles necessary to process each block.

A High-Resolution Demodulation Algorithm for FBG-FP Static-Strain Sensors Based on the Hilbert Transform and Cross Third-Order Cumulant

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Wenzhu Huang

2015-04-01

Full Text Available Static strain can be detected by measuring a cross-correlation of reflection spectra from two fiber Bragg gratings (FBGs. However, the static-strain measurement resolution is limited by the dominant Gaussian noise source when using this traditional method. This paper presents a novel static-strain demodulation algorithm for FBG-based Fabry-Perot interferometers (FBG-FPs. The Hilbert transform is proposed for changing the Gaussian distribution of the two FBG-FPs’ reflection spectra, and a cross third-order cumulant is used to use the results of the Hilbert transform and get a group of noise-vanished signals which can be used to accurately calculate the wavelength difference of the two FBG-FPs. The benefit by these processes is that Gaussian noise in the spectra can be suppressed completely in theory and a higher resolution can be reached. In order to verify the precision and flexibility of this algorithm, a detailed theory model and a simulation analysis are given, and an experiment is implemented. As a result, a static-strain resolution of 0.9 nε under laboratory environment condition is achieved, showing a higher resolution than the traditional cross-correlation method.

A numerical study of super-resolution through fast 3D wideband algorithm for scattering in highly-heterogeneous media

KAUST Repository

Létourneau, Pierre-David

2016-09-19

We present a wideband fast algorithm capable of accurately computing the full numerical solution of the problem of acoustic scattering of waves by multiple finite-sized bodies such as spherical scatterers in three dimensions. By full solution, we mean that no assumption (e.g. Rayleigh scattering, geometrical optics, weak scattering, Born single scattering, etc.) is necessary regarding the properties of the scatterers, their distribution or the background medium. The algorithm is also fast in the sense that it scales linearly with the number of unknowns. We use this algorithm to study the phenomenon of super-resolution in time-reversal refocusing in highly-scattering media recently observed experimentally (Lemoult et al., 2011), and provide numerical arguments towards the fact that such a phenomenon can be explained through a homogenization theory.

A comparison of graph- and kernel-based -omics data integration algorithms for classifying complex traits.

Science.gov (United States)

Yan, Kang K; Zhao, Hongyu; Pang, Herbert

2017-12-06

High-throughput sequencing data are widely collected and analyzed in the study of complex diseases in quest of improving human health. Well-studied algorithms mostly deal with single data source, and cannot fully utilize the potential of these multi-omics data sources. In order to provide a holistic understanding of human health and diseases, it is necessary to integrate multiple data sources. Several algorithms have been proposed so far, however, a comprehensive comparison of data integration algorithms for classification of binary traits is currently lacking. In this paper, we focus on two common classes of integration algorithms, graph-based that depict relationships with subjects denoted by nodes and relationships denoted by edges, and kernel-based that can generate a classifier in feature space. Our paper provides a comprehensive comparison of their performance in terms of various measurements of classification accuracy and computation time. Seven different integration algorithms, including graph-based semi-supervised learning, graph sharpening integration, composite association network, Bayesian network, semi-definite programming-support vector machine (SDP-SVM), relevance vector machine (RVM) and Ada-boost relevance vector machine are compared and evaluated with hypertension and two cancer data sets in our study. In general, kernel-based algorithms create more complex models and require longer computation time, but they tend to perform better than graph-based algorithms. The performance of graph-based algorithms has the advantage of being faster computationally. The empirical results demonstrate that composite association network, relevance vector machine, and Ada-boost RVM are the better performers. We provide recommendations on how to choose an appropriate algorithm for integrating data from multiple sources.

An Algorithm for Modelling the Impact of the Judicial Conflict-Resolution Process on Construction Investment

Directory of Open Access Journals (Sweden)

Andrej Bugajev

2018-01-01

Full Text Available In this article, the modelling of the judicial conflict-resolution process is considered from a construction investor’s point of view. Such modelling is important for improving the risk management for construction investors and supporting sustainable city development by supporting the development of rules regulating the construction process. Thus, this raises the problem of evaluation of different decisions and selection of the optimal one followed by distribution extraction. First, the example of such a process is analysed and schematically represented. Then, it is formalised as a graph, which is described in the form of a decision graph with cycles. We use some natural problem properties and provide the algorithm to convert this graph into a tree. Then, we propose the algorithm to evaluate profits for different scenarios with estimation of time, which is done by integration of an average daily costs function. Afterwards, the optimisation problem is solved and the optimal investor strategy is obtained—this allows one to extract the construction project profit distribution, which can be used for further analysis by standard risk (and other important information-evaluation techniques. The overall algorithm complexity is analysed, the computational experiment is performed and conclusions are formulated.

Resolution enhancement of low quality videos using a high-resolution frame

NARCIS (Netherlands)

Pham, T.Q.; Van Vliet, L.J.; Schutte, K.

2006-01-01

This paper proposes an example-based Super-Resolution (SR) algorithm of compressed videos in the Discrete Cosine Transform (DCT) domain. Input to the system is a Low-Resolution (LR) compressed video together with a High-Resolution (HR) still image of similar content. Using a training set of

AN ACTIVE-PASSIVE COMBINED ALGORITHM FOR HIGH SPATIAL RESOLUTION RETRIEVAL OF SOIL MOISTURE FROM SATELLITE SENSORS (Invited)

Science.gov (United States)

Lakshmi, V.; Mladenova, I. E.; Narayan, U.

2009-12-01

Soil moisture is known to be an essential factor in controlling the partitioning of rainfall into surface runoff and infiltration and solar energy into latent and sensible heat fluxes. Remote sensing has long proven its capability to obtain soil moisture in near real-time. However, at the present time we have the Advanced Scanning Microwave Radiometer (AMSR-E) on board NASA’s AQUA platform is the only satellite sensor that supplies a soil moisture product. AMSR-E coarse spatial resolution (~ 50 km at 6.9 GHz) strongly limits its applicability for small scale studies. A very promising technique for spatial disaggregation by combining radar and radiometer observations has been demonstrated by the authors using a methodology is based on the assumption that any change in measured brightness temperature and backscatter from one to the next time step is due primarily to change in soil wetness. The approach uses radiometric estimates of soil moisture at a lower resolution to compute the sensitivity of radar to soil moisture at the lower resolution. This estimate of sensitivity is then disaggregated using vegetation water content, vegetation type and soil texture information, which are the variables on which determine the radar sensitivity to soil moisture and are generally available at a scale of radar observation. This change detection algorithm is applied to several locations. We have used aircraft observed active and passive data over Walnut Creek watershed in Central Iowa in 2002; the Little Washita Watershed in Oklahoma in 2003 and the Murrumbidgee Catchment in southeastern Australia for 2006. All of these locations have different soils and land cover conditions which leads to a rigorous test of the disaggregation algorithm. Furthermore, we compare the derived high spatial resolution soil moisture to in-situ sampling and ground observation networks

Comparison of SeaWinds Backscatter Imaging Algorithms

Science.gov (United States)

Long, David G.

2017-01-01

This paper compares the performance and tradeoffs of various backscatter imaging algorithms for the SeaWinds scatterometer when multiple passes over a target are available. Reconstruction methods are compared with conventional gridding algorithms. In particular, the performance and tradeoffs in conventional ‘drop in the bucket’ (DIB) gridding at the intrinsic sensor resolution are compared to high-spatial-resolution imaging algorithms such as fine-resolution DIB and the scatterometer image reconstruction (SIR) that generate enhanced-resolution backscatter images. Various options for each algorithm are explored, including considering both linear and dB computation. The effects of sampling density and reconstruction quality versus time are explored. Both simulated and actual data results are considered. The results demonstrate the effectiveness of high-resolution reconstruction using SIR as well as its limitations and the limitations of DIB and fDIB. PMID:28828143

ON SOME TERMS DENOTING CREW MEMBERS ON DUBROVNIK SHIPS

Directory of Open Access Journals (Sweden)

Ariana Violić-Koprivec

2015-01-01

Full Text Available The paper discusses selected terms denoting crew members on Dubrovnik ships throughout the history. The titles of the most important crew members are analyzed based on the corpus of the 18th century documents, literary works, and technical literature. The goal is to determine which terms are typical of the Dubrovnik area, whether their meanings have become restricted or extended, and how they have disappeared or remained in use over the centuries. It is obvious that the importance of individual crew members and their positions changed with time. Their responsibilities occasionally overlapped, and certain terms for their positions coexisted as synonyms, either belonging to the standard or local, i.e. colloquial use. A comparative analysis has revealed some specific features of the Dubrovnik maritime terminology referring to the ship’s crew. The terms škrivan, nokjer, nostromo, pilot, gvardijan and dispensjer are lexemes specific for this area. This is confirmed by their use in literary works.

Super Resolution Algorithm for CCTVs

Science.gov (United States)

Gohshi, Seiichi

2015-03-01

Recently, security cameras and CCTV systems have become an important part of our daily lives. The rising demand for such systems has created business opportunities in this field, especially in big cities. Analogue CCTV systems are being replaced by digital systems, and HDTV CCTV has become quite common. HDTV CCTV can achieve images with high contrast and decent quality if they are clicked in daylight. However, the quality of an image clicked at night does not always have sufficient contrast and resolution because of poor lighting conditions. CCTV systems depend on infrared light at night to compensate for insufficient lighting conditions, thereby producing monochrome images and videos. However, these images and videos do not have high contrast and are blurred. We propose a nonlinear signal processing technique that significantly improves visual and image qualities (contrast and resolution) of low-contrast infrared images. The proposed method enables the use of infrared cameras for various purposes such as night shot and poor lighting environments under poor lighting conditions.

Airport Traffic Conflict Detection and Resolution Algorithm Evaluation

Science.gov (United States)

Jones, Denise R.; Chartrand, Ryan C.; Wilson, Sara R.; Commo, Sean A.; Otero, Sharon D.; Barker, Glover D.

2012-01-01

A conflict detection and resolution (CD&R) concept for the terminal maneuvering area (TMA) was evaluated in a fast-time batch simulation study at the National Aeronautics and Space Administration (NASA) Langley Research Center. The CD&R concept is being designed to enhance surface situation awareness and provide cockpit alerts of potential conflicts during runway, taxi, and low altitude air-to-air operations. The purpose of the study was to evaluate the performance of aircraft-based CD&R algorithms in the TMA, as a function of surveillance accuracy. This paper gives an overview of the CD&R concept, simulation study, and results. The Next Generation Air Transportation System (NextGen) concept for the year 2025 and beyond envisions the movement of large numbers of people and goods in a safe, efficient, and reliable manner [1]. NextGen will remove many of the constraints in the current air transportation system, support a wider range of operations, and provide an overall system capacity up to three times that of current operating levels. Emerging NextGen operational concepts [2], such as four-dimensional trajectory based airborne and surface operations, equivalent visual operations, and super density arrival and departure operations, require a different approach to air traffic management and as a result, a dramatic shift in the tasks, roles, and responsibilities for the flight deck and air traffic control (ATC) to ensure a safe, sustainable air transportation system.

Arrange and average algorithm for the retrieval of aerosol parameters from multiwavelength high-spectral-resolution lidar/Raman lidar data.

Science.gov (United States)

Chemyakin, Eduard; Müller, Detlef; Burton, Sharon; Kolgotin, Alexei; Hostetler, Chris; Ferrare, Richard

2014-11-01

We present the results of a feasibility study in which a simple, automated, and unsupervised algorithm, which we call the arrange and average algorithm, is used to infer microphysical parameters (complex refractive index, effective radius, total number, surface area, and volume concentrations) of atmospheric aerosol particles. The algorithm uses backscatter coefficients at 355, 532, and 1064 nm and extinction coefficients at 355 and 532 nm as input information. Testing of the algorithm is based on synthetic optical data that are computed from prescribed monomodal particle size distributions and complex refractive indices that describe spherical, primarily fine mode pollution particles. We tested the performance of the algorithm for the "3 backscatter (β)+2 extinction (α)" configuration of a multiwavelength aerosol high-spectral-resolution lidar (HSRL) or Raman lidar. We investigated the degree to which the microphysical results retrieved by this algorithm depends on the number of input backscatter and extinction coefficients. For example, we tested "3β+1α," "2β+1α," and "3β" lidar configurations. This arrange and average algorithm can be used in two ways. First, it can be applied for quick data processing of experimental data acquired with lidar. Fast automated retrievals of microphysical particle properties are needed in view of the enormous amount of data that can be acquired by the NASA Langley Research Center's airborne "3β+2α" High-Spectral-Resolution Lidar (HSRL-2). It would prove useful for the growing number of ground-based multiwavelength lidar networks, and it would provide an option for analyzing the vast amount of optical data acquired with a future spaceborne multiwavelength lidar. The second potential application is to improve the microphysical particle characterization with our existing inversion algorithm that uses Tikhonov's inversion with regularization. This advanced algorithm has recently undergone development to allow automated and

Large scale tracking algorithms

Energy Technology Data Exchange (ETDEWEB)

Hansen, Ross L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Love, Joshua Alan [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Melgaard, David Kennett [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Karelitz, David B. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Pitts, Todd Alan [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Zollweg, Joshua David [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Anderson, Dylan Z. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Nandy, Prabal [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Whitlow, Gary L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bender, Daniel A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Byrne, Raymond Harry [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-01-01

Low signal-to-noise data processing algorithms for improved detection, tracking, discrimination and situational threat assessment are a key research challenge. As sensor technologies progress, the number of pixels will increase signi cantly. This will result in increased resolution, which could improve object discrimination, but unfortunately, will also result in a significant increase in the number of potential targets to track. Many tracking techniques, like multi-hypothesis trackers, suffer from a combinatorial explosion as the number of potential targets increase. As the resolution increases, the phenomenology applied towards detection algorithms also changes. For low resolution sensors, "blob" tracking is the norm. For higher resolution data, additional information may be employed in the detection and classfication steps. The most challenging scenarios are those where the targets cannot be fully resolved, yet must be tracked and distinguished for neighboring closely spaced objects. Tracking vehicles in an urban environment is an example of such a challenging scenario. This report evaluates several potential tracking algorithms for large-scale tracking in an urban environment.

ELM: an Algorithm to Estimate the Alpha Abundance from Low-resolution Spectra

Science.gov (United States)

Bu, Yude; Zhao, Gang; Pan, Jingchang; Bharat Kumar, Yerra

2016-01-01

We have investigated a novel methodology using the extreme learning machine (ELM) algorithm to determine the α abundance of stars. Applying two methods based on the ELM algorithm—ELM+spectra and ELM+Lick indices—to the stellar spectra from the ELODIE database, we measured the α abundance with a precision better than 0.065 dex. By applying these two methods to the spectra with different signal-to-noise ratios (S/Ns) and different resolutions, we found that ELM+spectra is more robust against degraded resolution and ELM+Lick indices is more robust against variation in S/N. To further validate the performance of ELM, we applied ELM+spectra and ELM+Lick indices to SDSS spectra and estimated α abundances with a precision around 0.10 dex, which is comparable to the results given by the SEGUE Stellar Parameter Pipeline. We further applied ELM to the spectra of stars in Galactic globular clusters (M15, M13, M71) and open clusters (NGC 2420, M67, NGC 6791), and results show good agreement with previous studies (within 1σ). A comparison of the ELM with other widely used methods including support vector machine, Gaussian process regression, artificial neural networks, and linear least-squares regression shows that ELM is efficient with computational resources and more accurate than other methods.

ELM: AN ALGORITHM TO ESTIMATE THE ALPHA ABUNDANCE FROM LOW-RESOLUTION SPECTRA

International Nuclear Information System (INIS)

Bu, Yude; Zhao, Gang; Kumar, Yerra Bharat; Pan, Jingchang

2016-01-01

We have investigated a novel methodology using the extreme learning machine (ELM) algorithm to determine the α abundance of stars. Applying two methods based on the ELM algorithm—ELM+spectra and ELM+Lick indices—to the stellar spectra from the ELODIE database, we measured the α abundance with a precision better than 0.065 dex. By applying these two methods to the spectra with different signal-to-noise ratios (S/Ns) and different resolutions, we found that ELM+spectra is more robust against degraded resolution and ELM+Lick indices is more robust against variation in S/N. To further validate the performance of ELM, we applied ELM+spectra and ELM+Lick indices to SDSS spectra and estimated α abundances with a precision around 0.10 dex, which is comparable to the results given by the SEGUE Stellar Parameter Pipeline. We further applied ELM to the spectra of stars in Galactic globular clusters (M15, M13, M71) and open clusters (NGC 2420, M67, NGC 6791), and results show good agreement with previous studies (within 1σ). A comparison of the ELM with other widely used methods including support vector machine, Gaussian process regression, artificial neural networks, and linear least-squares regression shows that ELM is efficient with computational resources and more accurate than other methods

ELM: AN ALGORITHM TO ESTIMATE THE ALPHA ABUNDANCE FROM LOW-RESOLUTION SPECTRA

Energy Technology Data Exchange (ETDEWEB)

Bu, Yude [School of Mathematics and Statistics, Shandong University, Weihai, 264209, Shandong (China); Zhao, Gang; Kumar, Yerra Bharat [Key Laboratory for Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences, Beijing, 100012 (China); Pan, Jingchang, E-mail: ydbu@bao.ac.cn, E-mail: gzhao@nao.cas.cn [School of Mechanical, Electrical and Information Engineering, Shandong University, Weihai, 264209, Shandong (China)

2016-01-20

We have investigated a novel methodology using the extreme learning machine (ELM) algorithm to determine the α abundance of stars. Applying two methods based on the ELM algorithm—ELM+spectra and ELM+Lick indices—to the stellar spectra from the ELODIE database, we measured the α abundance with a precision better than 0.065 dex. By applying these two methods to the spectra with different signal-to-noise ratios (S/Ns) and different resolutions, we found that ELM+spectra is more robust against degraded resolution and ELM+Lick indices is more robust against variation in S/N. To further validate the performance of ELM, we applied ELM+spectra and ELM+Lick indices to SDSS spectra and estimated α abundances with a precision around 0.10 dex, which is comparable to the results given by the SEGUE Stellar Parameter Pipeline. We further applied ELM to the spectra of stars in Galactic globular clusters (M15, M13, M71) and open clusters (NGC 2420, M67, NGC 6791), and results show good agreement with previous studies (within 1σ). A comparison of the ELM with other widely used methods including support vector machine, Gaussian process regression, artificial neural networks, and linear least-squares regression shows that ELM is efficient with computational resources and more accurate than other methods.

Robust MST-Based Clustering Algorithm.

Science.gov (United States)

Liu, Qidong; Zhang, Ruisheng; Zhao, Zhili; Wang, Zhenghai; Jiao, Mengyao; Wang, Guangjing

2018-06-01

Minimax similarity stresses the connectedness of points via mediating elements rather than favoring high mutual similarity. The grouping principle yields superior clustering results when mining arbitrarily-shaped clusters in data. However, it is not robust against noises and outliers in the data. There are two main problems with the grouping principle: first, a single object that is far away from all other objects defines a separate cluster, and second, two connected clusters would be regarded as two parts of one cluster. In order to solve such problems, we propose robust minimum spanning tree (MST)-based clustering algorithm in this letter. First, we separate the connected objects by applying a density-based coarsening phase, resulting in a low-rank matrix in which the element denotes the supernode by combining a set of nodes. Then a greedy method is presented to partition those supernodes through working on the low-rank matrix. Instead of removing the longest edges from MST, our algorithm groups the data set based on the minimax similarity. Finally, the assignment of all data points can be achieved through their corresponding supernodes. Experimental results on many synthetic and real-world data sets show that our algorithm consistently outperforms compared clustering algorithms.

Learning from errors in super-resolution.

Science.gov (United States)

Tang, Yi; Yuan, Yuan

2014-11-01

A novel framework of learning-based super-resolution is proposed by employing the process of learning from the estimation errors. The estimation errors generated by different learning-based super-resolution algorithms are statistically shown to be sparse and uncertain. The sparsity of the estimation errors means most of estimation errors are small enough. The uncertainty of the estimation errors means the location of the pixel with larger estimation error is random. Noticing the prior information about the estimation errors, a nonlinear boosting process of learning from these estimation errors is introduced into the general framework of the learning-based super-resolution. Within the novel framework of super-resolution, a low-rank decomposition technique is used to share the information of different super-resolution estimations and to remove the sparse estimation errors from different learning algorithms or training samples. The experimental results show the effectiveness and the efficiency of the proposed framework in enhancing the performance of different learning-based algorithms.

LAI inversion algorithm based on directional reflectance kernels.

Science.gov (United States)

Tang, S; Chen, J M; Zhu, Q; Li, X; Chen, M; Sun, R; Zhou, Y; Deng, F; Xie, D

2007-11-01

Leaf area index (LAI) is an important ecological and environmental parameter. A new LAI algorithm is developed using the principles of ground LAI measurements based on canopy gap fraction. First, the relationship between LAI and gap fraction at various zenith angles is derived from the definition of LAI. Then, the directional gap fraction is acquired from a remote sensing bidirectional reflectance distribution function (BRDF) product. This acquisition is obtained by using a kernel driven model and a large-scale directional gap fraction algorithm. The algorithm has been applied to estimate a LAI distribution in China in mid-July 2002. The ground data acquired from two field experiments in Changbai Mountain and Qilian Mountain were used to validate the algorithm. To resolve the scale discrepancy between high resolution ground observations and low resolution remote sensing data, two TM images with a resolution approaching the size of ground plots were used to relate the coarse resolution LAI map to ground measurements. First, an empirical relationship between the measured LAI and a vegetation index was established. Next, a high resolution LAI map was generated using the relationship. The LAI value of a low resolution pixel was calculated from the area-weighted sum of high resolution LAIs composing the low resolution pixel. The results of this comparison showed that the inversion algorithm has an accuracy of 82%. Factors that may influence the accuracy are also discussed in this paper.

A high-resolution neutron spectra unfolding method using the Genetic Algorithm technique

CERN Document Server

Mukherjee, B

2002-01-01

The Bonner sphere spectrometers (BSS) are commonly used to determine the neutron spectra within various nuclear facilities. Sophisticated mathematical tools are used to unfold the neutron energy distribution from the output data of the BSS. This paper highlights a novel high-resolution neutron spectra-unfolding method using the Genetic Algorithm (GA) technique. The GA imitates the biological evolution process prevailing in the nature to solve complex optimisation problems. The GA method was utilised to evaluate the neutron energy distribution, average energy, fluence and equivalent dose rates at important work places of a DIDO class research reactor and a high-energy superconducting heavy ion cyclotron. The spectrometer was calibrated with a sup 2 sup 4 sup 1 Am/Be (alpha,n) neutron standard source. The results of the GA method agreed satisfactorily with the results obtained by using the well-known BUNKI neutron spectra unfolding code.

Fast generation of multiple resolution instances of raster data sets

DEFF Research Database (Denmark)

Arge, Lars; Haverkort, Herman; Tsirogiannis, Constantinos

2012-01-01

In many GIS applications it is important to study the characteristics of a raster data set at multiple resolutions. Often this is done by generating several coarser resolution rasters from a fine resolution raster. In this paper we describe efficient algorithms for different variants of this prob......In many GIS applications it is important to study the characteristics of a raster data set at multiple resolutions. Often this is done by generating several coarser resolution rasters from a fine resolution raster. In this paper we describe efficient algorithms for different variants...... in the main memory of the computer. We also provide two algorithms that solve this problem in external memory, that is when the input raster is larger than the main memory. The first external algorithm is very easy to implement and requires O(sort(N)) data block transfers from/to the external memory....... For this variant we describe an algorithm that runs in (U logN) time in internal memory, where U is the size of the output. We show how this algorithm can be adapted to perform efficiently in the external memory using O(sort(U)) data transfers from the disk. We have also implemented two of the presented algorithms...

A high resolution chromosome image processor for study purposes, NIRS-1000:CHROMO STUDY, and algorithm developing to classify radiation induced aberrations.

Science.gov (United States)

Yamamoto, M; Hayata, I; Furuta, S

1992-03-01

Since 1989 we have promoted a project to develop an automated scoring system of radiation induced chromosome aberrations. As a first step, a high resolution image processing system for study purposes, NIRS-1000:CHROMO STUDY, has been developed. It is composed of: (1) CHROMO MARKER whose main purpose is to mark on images to make image data base, (2) CHROMO ALGO whose purpose is algorithm development, and (3) METAPHASE RANKER whose purposes are metaphase finding and ranking with a high power objective lens. However, METAPHASE RANKER is presently under development. The system utilizes a high definition video system so as to realize the best spatial resolution that is achievable with an optical microscope using an objective lens (x 100, numerical aperture 1.4). The video camera has 1024 effective scan lines to realize 0.1 microns sampling on a specimen. The system resolution achieved on the hard copy is less than 0.3 microns on a specimen. A preliminary algorithm has been developed to classify the aberrations on the system using projection information of gray level. The preliminary test results on excellent 10 metaphases show that the correct classification ratio is 92.7%, that the detection rate of the aberrations is 83.3% and that the false positive rate is 6.1%.

Algorithm for Compressing Time-Series Data

Science.gov (United States)

Hawkins, S. Edward, III; Darlington, Edward Hugo

2012-01-01

An algorithm based on Chebyshev polynomials effects lossy compression of time-series data or other one-dimensional data streams (e.g., spectral data) that are arranged in blocks for sequential transmission. The algorithm was developed for use in transmitting data from spacecraft scientific instruments to Earth stations. In spite of its lossy nature, the algorithm preserves the information needed for scientific analysis. The algorithm is computationally simple, yet compresses data streams by factors much greater than two. The algorithm is not restricted to spacecraft or scientific uses: it is applicable to time-series data in general. The algorithm can also be applied to general multidimensional data that have been converted to time-series data, a typical example being image data acquired by raster scanning. However, unlike most prior image-data-compression algorithms, this algorithm neither depends on nor exploits the two-dimensional spatial correlations that are generally present in images. In order to understand the essence of this compression algorithm, it is necessary to understand that the net effect of this algorithm and the associated decompression algorithm is to approximate the original stream of data as a sequence of finite series of Chebyshev polynomials. For the purpose of this algorithm, a block of data or interval of time for which a Chebyshev polynomial series is fitted to the original data is denoted a fitting interval. Chebyshev approximation has two properties that make it particularly effective for compressing serial data streams with minimal loss of scientific information: The errors associated with a Chebyshev approximation are nearly uniformly distributed over the fitting interval (this is known in the art as the "equal error property"); and the maximum deviations of the fitted Chebyshev polynomial from the original data have the smallest possible values (this is known in the art as the "min-max property").

A Robust Parallel Algorithm for Combinatorial Compressed Sensing

Science.gov (United States)

Mendoza-Smith, Rodrigo; Tanner, Jared W.; Wechsung, Florian

2018-04-01

In previous work two of the authors have shown that a vector $x \\in \\mathbb{R}^n$ with at most $k Parallel-$\\ell_0$ decoding algorithm, where $\\mathrm{nnz}(A)$ denotes the number of nonzero entries in $A \\in \\mathbb{R}^{m \\times n}$. In this paper we present the Robust-$\\ell_0$ decoding algorithm, which robustifies Parallel-$\\ell_0$ when the sketch $Ax$ is corrupted by additive noise. This robustness is achieved by approximating the asymptotic posterior distribution of values in the sketch given its corrupted measurements. We provide analytic expressions that approximate these posteriors under the assumptions that the nonzero entries in the signal and the noise are drawn from continuous distributions. Numerical experiments presented show that Robust-$\\ell_0$ is superior to existing greedy and combinatorial compressed sensing algorithms in the presence of small to moderate signal-to-noise ratios in the setting of Gaussian signals and Gaussian additive noise.

Scalable Algorithms for Large High-Resolution Terrain Data

DEFF Research Database (Denmark)

Mølhave, Thomas; Agarwal, Pankaj K.; Arge, Lars Allan

2010-01-01

In this paper we demonstrate that the technology required to perform typical GIS computations on very large high-resolution terrain models has matured enough to be ready for use by practitioners. We also demonstrate the impact that high-resolution data has on common problems. To our knowledge, so...

High-resolution and super stacking of time-reversal mirrors in locating seismic sources

KAUST Repository

Cao, Weiping

2011-07-08

Time reversal mirrors can be used to backpropagate and refocus incident wavefields to their actual source location, with the subsequent benefits of imaging with high-resolution and super-stacking properties. These benefits of time reversal mirrors have been previously verified with computer simulations and laboratory experiments but not with exploration-scale seismic data. We now demonstrate the high-resolution and the super-stacking properties in locating seismic sources with field seismic data that include multiple scattering. Tests on both synthetic data and field data show that a time reversal mirror has the potential to exceed the Rayleigh resolution limit by factors of 4 or more. Results also show that a time reversal mirror has a significant resilience to strong Gaussian noise and that accurate imaging of source locations from passive seismic data can be accomplished with traces having signal-to-noise ratios as low as 0.001. Synthetic tests also demonstrate that time reversal mirrors can sometimes enhance the signal by a factor proportional to the square root of the product of the number of traces, denoted as N and the number of events in the traces. This enhancement property is denoted as super-stacking and greatly exceeds the classical signal-to-noise enhancement factor of. High-resolution and super-stacking are properties also enjoyed by seismic interferometry and reverse-time migration with the exact velocity model. © 2011 European Association of Geoscientists & Engineers.

Very low resolution face recognition problem.

Science.gov (United States)

Zou, Wilman W W; Yuen, Pong C

2012-01-01

This paper addresses the very low resolution (VLR) problem in face recognition in which the resolution of the face image to be recognized is lower than 16 × 16. With the increasing demand of surveillance camera-based applications, the VLR problem happens in many face application systems. Existing face recognition algorithms are not able to give satisfactory performance on the VLR face image. While face super-resolution (SR) methods can be employed to enhance the resolution of the images, the existing learning-based face SR methods do not perform well on such a VLR face image. To overcome this problem, this paper proposes a novel approach to learn the relationship between the high-resolution image space and the VLR image space for face SR. Based on this new approach, two constraints, namely, new data and discriminative constraints, are designed for good visuality and face recognition applications under the VLR problem, respectively. Experimental results show that the proposed SR algorithm based on relationship learning outperforms the existing algorithms in public face databases.

Resolution enhancement of low-quality videos using a high-resolution frame

Science.gov (United States)

Pham, Tuan Q.; van Vliet, Lucas J.; Schutte, Klamer

2006-01-01

This paper proposes an example-based Super-Resolution (SR) algorithm of compressed videos in the Discrete Cosine Transform (DCT) domain. Input to the system is a Low-Resolution (LR) compressed video together with a High-Resolution (HR) still image of similar content. Using a training set of corresponding LR-HR pairs of image patches from the HR still image, high-frequency details are transferred from the HR source to the LR video. The DCT-domain algorithm is much faster than example-based SR in spatial domain 6 because of a reduction in search dimensionality, which is a direct result of the compact and uncorrelated DCT representation. Fast searching techniques like tree-structure vector quantization 16 and coherence search1 are also key to the improved efficiency. Preliminary results on MJPEG sequence show promising result of the DCT-domain SR synthesis approach.

Single Image Super Resolution via Sparse Reconstruction

NARCIS (Netherlands)

Kruithof, M.C.; Eekeren, A.W.M. van; Dijk, J.; Schutte, K.

2012-01-01

High resolution sensors are required for recognition purposes. Low resolution sensors, however, are still widely used. Software can be used to increase the resolution of such sensors. One way of increasing the resolution of the images produced is using multi-frame super resolution algorithms.

A Cooperative Framework for Fireworks Algorithm.

Science.gov (United States)

Zheng, Shaoqiu; Li, Junzhi; Janecek, Andreas; Tan, Ying

2017-01-01

This paper presents a cooperative framework for fireworks algorithm (CoFFWA). A detailed analysis of existing fireworks algorithm (FWA) and its recently developed variants has revealed that ( i) the current selection strategy has the drawback that the contribution of the firework with the best fitness (denoted as core firework) overwhelms the contributions of all other fireworks (non-core fireworks) in the explosion operator, ( ii) the Gaussian mutation operator is not as effective as it is designed to be. To overcome these limitations, the CoFFWA is proposed, which significantly improves the exploitation capability by using an independent selection method and also increases the exploration capability by incorporating a crowdness-avoiding cooperative strategy among the fireworks. Experimental results on the CEC2013 benchmark functions indicate that CoFFWA outperforms the state-of-the-art FWA variants, artificial bee colony, differential evolution, and the standard particle swarm optimization SPSO2007/SPSO2011 in terms of convergence performance.

A Fast Algorithm for Image Super-Resolution from Blurred Observations

Directory of Open Access Journals (Sweden)

Ng Michael K

2006-01-01

Full Text Available We study the problem of reconstruction of a high-resolution image from several blurred low-resolution image frames. The image frames consist of blurred, decimated, and noisy versions of a high-resolution image. The high-resolution image is modeled as a Markov random field (MRF, and a maximum a posteriori (MAP estimation technique is used for the restoration. We show that with the periodic boundary condition, a high-resolution image can be restored efficiently by using fast Fourier transforms. We also apply the preconditioned conjugate gradient method to restore high-resolution images in the aperiodic boundary condition. Computer simulations are given to illustrate the effectiveness of the proposed approach.

Cost optimization model and its heuristic genetic algorithms

International Nuclear Information System (INIS)

Liu Wei; Wang Yongqing; Guo Jilin

1999-01-01

Interest and escalation are large quantity in proportion to the cost of nuclear power plant construction. In order to optimize the cost, the mathematics model of cost optimization for nuclear power plant construction was proposed, which takes the maximum net present value as the optimization goal. The model is based on the activity networks of the project and is an NP problem. A heuristic genetic algorithms (HGAs) for the model was introduced. In the algorithms, a solution is represented with a string of numbers each of which denotes the priority of each activity for assigned resources. The HGAs with this encoding method can overcome the difficulty which is harder to get feasible solutions when using the traditional GAs to solve the model. The critical path of the activity networks is figured out with the concept of predecessor matrix. An example was computed with the HGAP programmed in C language. The results indicate that the model is suitable for the objectiveness, the algorithms is effective to solve the model

Stratway: A Modular Approach to Strategic Conflict Resolution

Science.gov (United States)

Hagen, George E.; Butler, Ricky W.; Maddalon, Jeffrey M.

2011-01-01

In this paper we introduce Stratway, a modular approach to finding long-term strategic resolutions to conflicts between aircraft. The modular approach provides both advantages and disadvantages. Our primary concern is to investigate the implications on the verification of safety-critical properties of a strategic resolution algorithm. By partitioning the problem into verifiable modules much stronger verification claims can be established. Since strategic resolution involves searching for solutions over an enormous state space, Stratway, like most similar algorithms, searches these spaces by applying heuristics, which present especially difficult verification challenges. An advantage of a modular approach is that it makes a clear distinction between the resolution function and the trajectory generation function. This allows the resolution computation to be independent of any particular vehicle. The Stratway algorithm was developed in both Java and C++ and is available through a open source license. Additionally there is a visualization application that is helpful when analyzing and quickly creating conflict scenarios.

Fourier rebinning algorithm for inverse geometry CT.

Science.gov (United States)

Mazin, Samuel R; Pele, Norbert J

2008-11-01

Inverse geometry computed tomography (IGCT) is a new type of volumetric CT geometry that employs a large array of x-ray sources opposite a smaller detector array. Volumetric coverage and high isotropic resolution produce very large data sets and therefore require a computationally efficient three-dimensional reconstruction algorithm. The purpose of this work was to adapt and evaluate a fast algorithm based on Defrise's Fourier rebinning (FORE), originally developed for positron emission tomography. The results were compared with the average of FDK reconstructions from each source row. The FORE algorithm is an order of magnitude faster than the FDK-type method for the case of 11 source rows. In the center of the field-of-view both algorithms exhibited the same resolution and noise performance. FORE exhibited some resolution loss (and less noise) in the periphery of the field-of-view. FORE appears to be a fast and reasonably accurate reconstruction method for IGCT.

A universal optimization strategy for ant colony optimization algorithms based on the Physarum-inspired mathematical model

International Nuclear Information System (INIS)

Zhang, Zili; Gao, Chao; Liu, Yuxin; Qian, Tao

2014-01-01

Ant colony optimization (ACO) algorithms often fall into the local optimal solution and have lower search efficiency for solving the travelling salesman problem (TSP). According to these shortcomings, this paper proposes a universal optimization strategy for updating the pheromone matrix in the ACO algorithms. The new optimization strategy takes advantages of the unique feature of critical paths reserved in the process of evolving adaptive networks of the Physarum-inspired mathematical model (PMM). The optimized algorithms, denoted as PMACO algorithms, can enhance the amount of pheromone in the critical paths and promote the exploitation of the optimal solution. Experimental results in synthetic and real networks show that the PMACO algorithms are more efficient and robust than the traditional ACO algorithms, which are adaptable to solve the TSP with single or multiple objectives. Meanwhile, we further analyse the influence of parameters on the performance of the PMACO algorithms. Based on these analyses, the best values of these parameters are worked out for the TSP. (paper)

Anaphora Resolution Algorithm for Sanskrit

Science.gov (United States)

Pralayankar, Pravin; Devi, Sobha Lalitha

This paper presents an algorithm, which identifies different types of pronominal and its antecedents in Sanskrit, an Indo-European language. The computational grammar implemented here uses very familiar concepts such as clause, subject, object etc., which are identified with the help of morphological information and concepts such as precede and follow. It is well known that natural languages contain anaphoric expressions, gaps and elliptical constructions of various kinds and that understanding of natural languages involves assignment of interpretations to these elements. Therefore, it is only to be expected that natural language understanding systems must have the necessary mechanism to resolve the same. The method we adopt here for resolving the anaphors is by exploiting the morphological richness of the language. The system is giving encouraging results when tested with a small corpus.

Parallelization of a blind deconvolution algorithm

Science.gov (United States)

Matson, Charles L.; Borelli, Kathy J.

2006-09-01

Often it is of interest to deblur imagery in order to obtain higher-resolution images. Deblurring requires knowledge of the blurring function - information that is often not available separately from the blurred imagery. Blind deconvolution algorithms overcome this problem by jointly estimating both the high-resolution image and the blurring function from the blurred imagery. Because blind deconvolution algorithms are iterative in nature, they can take minutes to days to deblur an image depending how many frames of data are used for the deblurring and the platforms on which the algorithms are executed. Here we present our progress in parallelizing a blind deconvolution algorithm to increase its execution speed. This progress includes sub-frame parallelization and a code structure that is not specialized to a specific computer hardware architecture.

A novel super-resolution camera model

Science.gov (United States)

Shao, Xiaopeng; Wang, Yi; Xu, Jie; Wang, Lin; Liu, Fei; Luo, Qiuhua; Chen, Xiaodong; Bi, Xiangli

2015-05-01

Aiming to realize super resolution(SR) to single image and video reconstruction, a super resolution camera model is proposed for the problem that the resolution of the images obtained by traditional cameras behave comparatively low. To achieve this function we put a certain driving device such as piezoelectric ceramics in the camera. By controlling the driving device, a set of continuous low resolution(LR) images can be obtained and stored instantaneity, which reflect the randomness of the displacements and the real-time performance of the storage very well. The low resolution image sequences have different redundant information and some particular priori information, thus it is possible to restore super resolution image factually and effectively. The sample method is used to derive the reconstruction principle of super resolution, which analyzes the possible improvement degree of the resolution in theory. The super resolution algorithm based on learning is used to reconstruct single image and the variational Bayesian algorithm is simulated to reconstruct the low resolution images with random displacements, which models the unknown high resolution image, motion parameters and unknown model parameters in one hierarchical Bayesian framework. Utilizing sub-pixel registration method, a super resolution image of the scene can be reconstructed. The results of 16 images reconstruction show that this camera model can increase the image resolution to 2 times, obtaining images with higher resolution in currently available hardware levels.

Resolution analysis by random probing

NARCIS (Netherlands)

Fichtner, Andreas; van Leeuwen, T.

2015-01-01

We develop and apply methods for resolution analysis in tomography, based on stochastic probing of the Hessian or resolution operators. Key properties of our methods are (i) low algorithmic complexity and easy implementation, (ii) applicability to any tomographic technique, including full‐waveform

Ultra high resolution soft x-ray tomography

International Nuclear Information System (INIS)

Haddad, W.S.; Trebes, J.E.; Goodman, D.M.

1995-01-01

Ultra high resolution three dimensional images of a microscopic test object were made with soft x-rays using a scanning transmission x-ray microscope. The test object consisted of two different patterns of gold bars on silicon nitride windows that were separated by ∼5μm. A series of nine 2-D images of the object were recorded at angles between -50 to +55 degrees with respect to the beam axis. The projections were then combined tomographically to form a 3-D image by means of an algebraic reconstruction technique (ART) algorithm. A transverse resolution of ∼1000 Angstrom was observed. Artifacts in the reconstruction limited the overall depth resolution to ∼6000 Angstrom, however some features were clearly reconstructed with a depth resolution of ∼1000 Angstrom. A specially modified ART algorithm and a constrained conjugate gradient (CCG) code were also developed as improvements over the standard ART algorithm. Both of these methods made significant improvements in the overall depth resolution bringing it down to ∼1200 Angstrom overall. Preliminary projection data sets were also recorded with both dry and re-hydrated human sperm cells over a similar angular range

Ultra high resolution soft x-ray tomography

International Nuclear Information System (INIS)

Haddad, W.S.; Trebes, J.E.; Goodman, D.M.; Lee, H.R.; McNulty, I.; Zalensky, A.O.

1995-01-01

Ultra high resolution three dimensional images of a microscopic test object were made with soft x-rays using a scanning transmission x-ray microscope. The test object consisted of two different patterns of gold bars on silicon nitride windows that were separated by ∼5 microm. A series of nine 2-D images of the object were recorded at angles between -50 to +55 degrees with respect to the beam axis. The projections were then combined tomographically to form a 3-D image by means of an algebraic reconstruction technique (ART) algorithm. A transverse resolution of ∼ 1,000 angstrom was observed. Artifacts in the reconstruction limited the overall depth resolution to ∼ 6,000 angstrom, however some features were clearly reconstructed with a depth resolution of ∼ 1,000 angstrom. A specially modified ART algorithm and a constrained conjugate gradient (CCG) code were also developed as improvements over the standard ART algorithm. Both of these methods made significant improvements in the overall depth resolution, bringing it down to ∼ 1,200 angstrom overall. Preliminary projection data sets were also recorded with both dry and re-hydrated human sperm cells over a similar angular range

A Novel 2D Image Compression Algorithm Based on Two Levels DWT and DCT Transforms with Enhanced Minimize-Matrix-Size Algorithm for High Resolution Structured Light 3D Surface Reconstruction

Science.gov (United States)

Siddeq, M. M.; Rodrigues, M. A.

2015-09-01

Image compression techniques are widely used on 2D image 2D video 3D images and 3D video. There are many types of compression techniques and among the most popular are JPEG and JPEG2000. In this research, we introduce a new compression method based on applying a two level discrete cosine transform (DCT) and a two level discrete wavelet transform (DWT) in connection with novel compression steps for high-resolution images. The proposed image compression algorithm consists of four steps. (1) Transform an image by a two level DWT followed by a DCT to produce two matrices: DC- and AC-Matrix, or low and high frequency matrix, respectively, (2) apply a second level DCT on the DC-Matrix to generate two arrays, namely nonzero-array and zero-array, (3) apply the Minimize-Matrix-Size algorithm to the AC-Matrix and to the other high-frequencies generated by the second level DWT, (4) apply arithmetic coding to the output of previous steps. A novel decompression algorithm, Fast-Match-Search algorithm (FMS), is used to reconstruct all high-frequency matrices. The FMS-algorithm computes all compressed data probabilities by using a table of data, and then using a binary search algorithm for finding decompressed data inside the table. Thereafter, all decoded DC-values with the decoded AC-coefficients are combined in one matrix followed by inverse two levels DCT with two levels DWT. The technique is tested by compression and reconstruction of 3D surface patches. Additionally, this technique is compared with JPEG and JPEG2000 algorithm through 2D and 3D root-mean-square-error following reconstruction. The results demonstrate that the proposed compression method has better visual properties than JPEG and JPEG2000 and is able to more accurately reconstruct surface patches in 3D.

MRI isotropic resolution reconstruction from two orthogonal scans

Science.gov (United States)

Tamez-Pena, Jose G.; Totterman, Saara; Parker, Kevin J.

2001-07-01

An algorithm for the reconstructions of ISO-resolution volumetric MR data sets from two standard orthogonal MR scans having anisotropic resolution has been developed. The reconstruction algorithm starts by registering a pair of orthogonal volumetric MR data sets. The registration is done by maximizing the correlation between the gradient magnitude using a simple translation-rotation model in a multi-resolution approach. Then algorithm assumes that the individual voxels on the MR data are an average of the magnetic resonance properties of an elongated imaging volume. Then, the process is modeled as the projection of MR properties into a single sensor. This model allows the derivation of a set of linear equations that can be used to recover the MR properties of every single voxel in the SO-resolution volume given only two orthogonal MR scans. Projections on convex sets (POCS) was used to solve the set of linear equations. Experimental results show the advantage of having a ISO-resolution reconstructions for the visualization and analysis of small and thin muscular structures.

RNA folding kinetics using Monte Carlo and Gillespie algorithms.

Science.gov (United States)

Clote, Peter; Bayegan, Amir H

2018-04-01

RNA secondary structure folding kinetics is known to be important for the biological function of certain processes, such as the hok/sok system in E. coli. Although linear algebra provides an exact computational solution of secondary structure folding kinetics with respect to the Turner energy model for tiny ([Formula: see text]20 nt) RNA sequences, the folding kinetics for larger sequences can only be approximated by binning structures into macrostates in a coarse-grained model, or by repeatedly simulating secondary structure folding with either the Monte Carlo algorithm or the Gillespie algorithm. Here we investigate the relation between the Monte Carlo algorithm and the Gillespie algorithm. We prove that asymptotically, the expected time for a K-step trajectory of the Monte Carlo algorithm is equal to [Formula: see text] times that of the Gillespie algorithm, where [Formula: see text] denotes the Boltzmann expected network degree. If the network is regular (i.e. every node has the same degree), then the mean first passage time (MFPT) computed by the Monte Carlo algorithm is equal to MFPT computed by the Gillespie algorithm multiplied by [Formula: see text]; however, this is not true for non-regular networks. In particular, RNA secondary structure folding kinetics, as computed by the Monte Carlo algorithm, is not equal to the folding kinetics, as computed by the Gillespie algorithm, although the mean first passage times are roughly correlated. Simulation software for RNA secondary structure folding according to the Monte Carlo and Gillespie algorithms is publicly available, as is our software to compute the expected degree of the network of secondary structures of a given RNA sequence-see http://bioinformatics.bc.edu/clote/RNAexpNumNbors .

Resolution Enhancement Method Used for Force Sensing Resistor Array

Directory of Open Access Journals (Sweden)

Karen Flores De Jesus

2015-01-01

Full Text Available Tactile sensors are one of the major devices that enable robotic systems to interact with the surrounding environment. This research aims to propose a mathematical model to describe the behavior of a tactile sensor based on experimental and statistical analyses and moreover to develop a versatile algorithm that can be applied to different tactile sensor arrays to enhance the limited resolution. With the proposed algorithm, the resolution can be increased up to twenty times if multiple measurements are available. To verify if the proposed algorithm can be used for tactile sensor arrays that are used in robotic system, a 16×10 force sensing array (FSR is adopted. The acquired two-dimensional measurements were processed by a resolution enhancement method (REM to enhance the resolution, which can be used to improve the resolution for single image or multiple measurements. As a result, the resolution of the sensor is increased and it can be used as synthetic skin to identify accurate shapes of objects and applied forces.

Automated Conflict Resolution For Air Traffic Control

Science.gov (United States)

Erzberger, Heinz

2005-01-01

The ability to detect and resolve conflicts automatically is considered to be an essential requirement for the next generation air traffic control system. While systems for automated conflict detection have been used operationally by controllers for more than 20 years, automated resolution systems have so far not reached the level of maturity required for operational deployment. Analytical models and algorithms for automated resolution have been traffic conditions to demonstrate that they can handle the complete spectrum of conflict situations encountered in actual operations. The resolution algorithm described in this paper was formulated to meet the performance requirements of the Automated Airspace Concept (AAC). The AAC, which was described in a recent paper [1], is a candidate for the next generation air traffic control system. The AAC's performance objectives are to increase safety and airspace capacity and to accommodate user preferences in flight operations to the greatest extent possible. In the AAC, resolution trajectories are generated by an automation system on the ground and sent to the aircraft autonomously via data link .The algorithm generating the trajectories must take into account the performance characteristics of the aircraft, the route structure of the airway system, and be capable of resolving all types of conflicts for properly equipped aircraft without requiring supervision and approval by a controller. Furthermore, the resolution trajectories should be compatible with the clearances, vectors and flight plan amendments that controllers customarily issue to pilots in resolving conflicts. The algorithm described herein, although formulated specifically to meet the needs of the AAC, provides a generic engine for resolving conflicts. Thus, it can be incorporated into any operational concept that requires a method for automated resolution, including concepts for autonomous air to air resolution.

Speckle imaging algorithms for planetary imaging

Energy Technology Data Exchange (ETDEWEB)

Johansson, E. [Lawrence Livermore National Lab., CA (United States)

1994-11-15

I will discuss the speckle imaging algorithms used to process images of the impact sites of the collision of comet Shoemaker-Levy 9 with Jupiter. The algorithms use a phase retrieval process based on the average bispectrum of the speckle image data. High resolution images are produced by estimating the Fourier magnitude and Fourier phase of the image separately, then combining them and inverse transforming to achieve the final result. I will show raw speckle image data and high-resolution image reconstructions from our recent experiment at Lick Observatory.

Single breath-hold real-time cine MR imaging: improved temporal resolution using generalized autocalibrating partially parallel acquisition (GRAPPA) algorithm

International Nuclear Information System (INIS)

Wintersperger, Bernd J.; Nikolaou, Konstantin; Dietrich, Olaf; Reiser, Maximilian F.; Schoenberg, Stefan O.; Rieber, Johannes; Nittka, Matthias

2003-01-01

The purpose of this study was to test parallel imaging techniques for improvement of temporal resolution in multislice single breath-hold real-time cine steady-state free precession (SSFP) in comparison with standard segmented single-slice SSFP techniques. Eighteen subjects were examined on a 1.5-T scanner using a multislice real-time cine SSFP technique using the GRAPPA algorithm. Global left ventricular parameters (EDV, ESV, SV, EF) were evaluated and results compared with a standard segmented single-slice SSFP technique. Results for EDV (r=0.93), ESV (r=0.99), SV (r=0.83), and EF (r=0.99) of real-time multislice SSFP imaging showed a high correlation with results of segmented SSFP acquisitions. Systematic differences between both techniques were statistically non-significant. Single breath-hold multislice techniques using GRAPPA allow for improvement of temporal resolution and for accurate assessment of global left ventricular functional parameters. (orig.)

Chandra ACIS Sub-pixel Resolution

Science.gov (United States)

Kim, Dong-Woo; Anderson, C. S.; Mossman, A. E.; Allen, G. E.; Fabbiano, G.; Glotfelty, K. J.; Karovska, M.; Kashyap, V. L.; McDowell, J. C.

2011-05-01

We investigate how to achieve the best possible ACIS spatial resolution by binning in ACIS sub-pixel and applying an event repositioning algorithm after removing pixel-randomization from the pipeline data. We quantitatively assess the improvement in spatial resolution by (1) measuring point source sizes and (2) detecting faint point sources. The size of a bright (but no pile-up), on-axis point source can be reduced by about 20-30%. With the improve resolution, we detect 20% more faint sources when embedded on the extended, diffuse emission in a crowded field. We further discuss the false source rate of about 10% among the newly detected sources, using a few ultra-deep observations. We also find that the new algorithm does not introduce a grid structure by an aliasing effect for dithered observations and does not worsen the positional accuracy

A micro-hydrology computation ordering algorithm

Science.gov (United States)

Croley, Thomas E.

1980-11-01

Discrete-distributed-parameter models are essential for watershed modelling where practical consideration of spatial variations in watershed properties and inputs is desired. Such modelling is necessary for analysis of detailed hydrologic impacts from management strategies and land-use effects. Trade-offs between model validity and model complexity exist in resolution of the watershed. Once these are determined, the watershed is then broken into sub-areas which each have essentially spatially-uniform properties. Lumped-parameter (micro-hydrology) models are applied to these sub-areas and their outputs are combined through the use of a computation ordering technique, as illustrated by many discrete-distributed-parameter hydrology models. Manual ordering of these computations requires fore-thought, and is tedious, error prone, sometimes storage intensive and least adaptable to changes in watershed resolution. A programmable algorithm for ordering micro-hydrology computations is presented that enables automatic ordering of computations within the computer via an easily understood and easily implemented "node" definition, numbering and coding scheme. This scheme and the algorithm are detailed in logic flow-charts and an example application is presented. Extensions and modifications of the algorithm are easily made for complex geometries or differing microhydrology models. The algorithm is shown to be superior to manual ordering techniques and has potential use in high-resolution studies.

A micro-hydrology computation ordering algorithm

International Nuclear Information System (INIS)

Croley, T.E. II

1980-01-01

Discrete-distributed-parameter models are essential for watershed modelling where practical consideration of spatial variations in watershed properties and inputs is desired. Such modelling is necessary for analysis of detailed hydrologic impacts from management strategies and land-use effects. Trade-offs between model validity and model complexity exist in resolution of the watershed. Once these are determined, the watershed is then broken into sub-areas which each have essentially spatially-uniform properties. Lumped-parameter (micro-hydrology) models are applied to these sub-areas and their outputs are combined through the use of a computation ordering technique, as illustrated by many discrete-distributed-parameter hydrology models. Manual ordering of these computations requires fore-thought, and is tedious, error prone, sometimes storage intensive and least adaptable to changes in watershed resolution. A programmable algorithm for ordering micro-hydrology computations is presented that enables automatic ordering of computations within the computer via an easily understood and easily implemented node definition, numbering and coding scheme. This scheme and the algorithm are detailed in logic flow-charts and an example application is presented. Extensions and modifications of the algorithm are easily made for complex geometries or differing micro-hydrology models. The algorithm is shown to be superior to manual ordering techniques and has potential use in high-resolution studies. (orig.)

Denotational Aspects of Untyped Normalization by Evaluation

DEFF Research Database (Denmark)

Filinski, Andrzej; Rohde, Henning Korsholm

2005-01-01

of soundness (the output term, if any, is in normal form and ß-equivalent to the input term); identification (ß-equivalent terms are mapped to the same result); and completeness (the function is defined for all terms that do have normal forms). We also show how the semantic construction enables a simple yet...... formal correctness proof for the normalization algorithm, expressed as a functional program in an ML-like, call-by-value language. Finally, we generalize the construction to produce an infinitary variant of normal forms, namely Böhm trees. We show that the three-part characterization of correctness...

Towards Compatible and Interderivable Semantic Specifications for the Scheme Programming Language, Part I: Denotational Semantics, Natural Semantics, and Abstract Machines

DEFF Research Database (Denmark)

Danvy, Olivier

2009-01-01

We derive two big-step abstract machines, a natural semantics, and the valuation function of a denotational semantics based on the small-step abstract machine for Core Scheme presented by Clinger at PLDI'98. Starting from a functional implementation of this small-step abstract machine, (1) we fus...

Solving Flexible Job-Shop Scheduling Problem Using Gravitational Search Algorithm and Colored Petri Net

Directory of Open Access Journals (Sweden)

Behnam Barzegar

2012-01-01

Full Text Available Scheduled production system leads to avoiding stock accumulations, losses reduction, decreasing or even eliminating idol machines, and effort to better benefitting from machines for on time responding customer orders and supplying requested materials in suitable time. In flexible job-shop scheduling production systems, we could reduce time and costs by transferring and delivering operations on existing machines, that is, among NP-hard problems. The scheduling objective minimizes the maximal completion time of all the operations, which is denoted by Makespan. Different methods and algorithms have been presented for solving this problem. Having a reasonable scheduled production system has significant influence on improving effectiveness and attaining to organization goals. In this paper, new algorithm were proposed for flexible job-shop scheduling problem systems (FJSSP-GSPN that is based on gravitational search algorithm (GSA. In the proposed method, the flexible job-shop scheduling problem systems was modeled by color Petri net and CPN tool and then a scheduled job was programmed by GSA algorithm. The experimental results showed that the proposed method has reasonable performance in comparison with other algorithms.

Evaluation of deep neural networks for single image super-resolution in a maritime context

NARCIS (Netherlands)

Nieuwenhuizen, R.P.J.; Kruithof, M.; Schutte, K.

2017-01-01

High resolution imagery is of crucial importance for the performance on visual recognition tasks. Super-resolution (SR) reconstruction algorithms aim to enhance the image resolution beyond the capability of the image sensor being used. Traditional SR algorithms approach this inverse problem using

Resolution-recovery-embedded image reconstruction for a high-resolution animal SPECT system.

Science.gov (United States)

Zeraatkar, Navid; Sajedi, Salar; Farahani, Mohammad Hossein; Arabi, Hossein; Sarkar, Saeed; Ghafarian, Pardis; Rahmim, Arman; Ay, Mohammad Reza

2014-11-01

The small-animal High-Resolution SPECT (HiReSPECT) is a dedicated dual-head gamma camera recently designed and developed in our laboratory for imaging of murine models. Each detector is composed of an array of 1.2 × 1.2 mm(2) (pitch) pixelated CsI(Na) crystals. Two position-sensitive photomultiplier tubes (H8500) are coupled to each head's crystal. In this paper, we report on a resolution-recovery-embedded image reconstruction code applicable to the system and present the experimental results achieved using different phantoms and mouse scans. Collimator-detector response functions (CDRFs) were measured via a pixel-driven method using capillary sources at finite distances from the head within the field of view (FOV). CDRFs were then fitted by independent Gaussian functions. Thereafter, linear interpolations were applied to the standard deviation (σ) values of the fitted Gaussians, yielding a continuous map of CDRF at varying distances from the head. A rotation-based maximum-likelihood expectation maximization (MLEM) method was used for reconstruction. A fast rotation algorithm was developed to rotate the image matrix according to the desired angle by means of pre-generated rotation maps. The experiments demonstrated improved resolution utilizing our resolution-recovery-embedded image reconstruction. While the full-width at half-maximum (FWHM) radial and tangential resolution measurements of the system were over 2 mm in nearly all positions within the FOV without resolution recovery, reaching around 2.5 mm in some locations, they fell below 1.8 mm everywhere within the FOV using the resolution-recovery algorithm. The noise performance of the system was also acceptable; the standard deviation of the average counts per voxel in the reconstructed images was 6.6% and 8.3% without and with resolution recovery, respectively. Copyright © 2014 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Comparison of two global digital algorithms for Minkowski tensor estimation

DEFF Research Database (Denmark)

The geometry of real world objects can be described by Minkowski tensors. Algorithms have been suggested to approximate Minkowski tensors if only a binary image of the object is available. This paper presents implementations of two such algorithms. The theoretical convergence properties...... are confirmed by simulations on test sets, and recommendations for input arguments of the algorithms are given. For increasing resolutions, we obtain more accurate estimators for the Minkowski tensors. Digitisations of more complicated objects are shown to require higher resolutions....

High-spatial-resolution localization algorithm based on cascade deconvolution in a distributed Sagnac interferometer invasion monitoring system.

Science.gov (United States)

Pi, Shaohua; Wang, Bingjie; Zhao, Jiang; Sun, Qi

2016-10-10

In the Sagnac fiber optic interferometer system, the phase difference signal can be illustrated as a convolution of the waveform of the invasion with its occurring-position-associated transfer function h(t); deconvolution is introduced to improve the spatial resolution of the localization. In general, to get a 26 m spatial resolution at a sampling rate of 4×106  s-1, the algorithm should mainly go through three steps after the preprocessing operations. First, the decimated phase difference signal is transformed from the time domain into the real cepstrum domain, where a probable region of invasion distance can be ascertained. Second, a narrower region of invasion distance is acquired by coarsely assuming and sweeping a transfer function h(t) within the probable region and examining where the restored invasion waveform x(t) gets its minimum standard deviation. Third, fine sweeping the narrow region point by point with the same criteria is used to get the final localization. Also, the original waveform of invasion can be restored for the first time as a by-product, which provides more accurate and pure characteristics for further processing, such as subsequent pattern recognition.

Genetic Algorithm Applied to the Eigenvalue Equalization Filtered-x LMS Algorithm (EE-FXLMS

Directory of Open Access Journals (Sweden)

Stephan P. Lovstedt

2008-01-01

Full Text Available The FXLMS algorithm, used extensively in active noise control (ANC, exhibits frequency-dependent convergence behavior. This leads to degraded performance for time-varying tonal noise and noise with multiple stationary tones. Previous work by the authors proposed the eigenvalue equalization filtered-x least mean squares (EE-FXLMS algorithm. For that algorithm, magnitude coefficients of the secondary path transfer function are modified to decrease variation in the eigenvalues of the filtered-x autocorrelation matrix, while preserving the phase, giving faster convergence and increasing overall attenuation. This paper revisits the EE-FXLMS algorithm, using a genetic algorithm to find magnitude coefficients that give the least variation in eigenvalues. This method overcomes some of the problems with implementing the EE-FXLMS algorithm arising from finite resolution of sampled systems. Experimental control results using the original secondary path model, and a modified secondary path model for both the previous implementation of EE-FXLMS and the genetic algorithm implementation are compared.

A Non-static Data Layout Enhancing Parallelism and Vectorization in Sparse Grid Algorithms

KAUST Repository

Buse, Gerrit

2012-06-01

The name sparse grids denotes a highly space-efficient, grid-based numerical technique to approximate high-dimensional functions. Although employed in a broad spectrum of applications from different fields, there have only been few tries to use it in real time visualization (e.g. [1]), due to complex data structures and long algorithm runtime. In this work we present a novel approach inspired by principles of I/0-efficient algorithms. Locally applied coefficient permutations lead to improved cache performance and facilitate the use of vector registers for our sparse grid benchmark problem hierarchization. Based on the compact data structure proposed for regular sparse grids in [2], we developed a new algorithm that outperforms existing implementations on modern multi-core systems by a factor of 37 for a grid size of 127 million points. For larger problems the speedup is even increasing, and with execution times below 1 s, sparse grids are well-suited for visualization applications. Furthermore, we point out how a broad class of sparse grid algorithms can benefit from our approach. © 2012 IEEE.

A hybrid genetic algorithm for the distributed permutation flowshop scheduling problem

Directory of Open Access Journals (Sweden)

Jian Gao

2011-08-01

Full Text Available Distributed Permutation Flowshop Scheduling Problem (DPFSP is a newly proposed scheduling problem, which is a generalization of classical permutation flow shop scheduling problem. The DPFSP is NP-hard in general. It is in the early stages of studies on algorithms for solving this problem. In this paper, we propose a GA-based algorithm, denoted by GA_LS, for solving this problem with objective to minimize the maximum completion time. In the proposed GA_LS, crossover and mutation operators are designed to make it suitable for the representation of DPFSP solutions, where the set of partial job sequences is employed. Furthermore, GA_LS utilizes an efficient local search method to explore neighboring solutions. The local search method uses three proposed rules that move jobs within a factory or between two factories. Intensive experiments on the benchmark instances, extended from Taillard instances, are carried out. The results indicate that the proposed hybrid genetic algorithm can obtain better solutions than all the existing algorithms for the DPFSP, since it obtains better relative percentage deviation and differences of the results are also statistically significant. It is also seen that best-known solutions for most instances are updated by our algorithm. Moreover, we also show the efficiency of the GA_LS by comparing with similar genetic algorithms with the existing local search methods.

Deconvolution algorithms applied in ultrasonics

International Nuclear Information System (INIS)

Perrot, P.

1993-12-01

In a complete system of acquisition and processing of ultrasonic signals, it is often necessary at one stage to use some processing tools to get rid of the influence of the different elements of that system. By that means, the final quality of the signals in terms of resolution is improved. There are two main characteristics of ultrasonic signals which make this task difficult. Firstly, the signals generated by transducers are very often non-minimum phase. The classical deconvolution algorithms are unable to deal with such characteristics. Secondly, depending on the medium, the shape of the propagating pulse is evolving. The spatial invariance assumption often used in classical deconvolution algorithms is rarely valid. Many classical algorithms, parametric and non-parametric, have been investigated: the Wiener-type, the adaptive predictive techniques, the Oldenburg technique in the frequency domain, the minimum variance deconvolution. All the algorithms have been firstly tested on simulated data. One specific experimental set-up has also been analysed. Simulated and real data has been produced. This set-up demonstrated the interest in applying deconvolution, in terms of the achieved resolution. (author). 32 figs., 29 refs

Inverse transformation algorithm of transient electromagnetic field and its high-resolution continuous imaging interpretation method

International Nuclear Information System (INIS)

Qi, Zhipeng; Li, Xiu; Lu, Xushan; Zhang, Yingying; Yao, Weihua

2015-01-01

We introduce a new and potentially useful method for wave field inverse transformation and its application in transient electromagnetic method (TEM) 3D interpretation. The diffusive EM field is known to have a unique integral representation in terms of a fictitious wave field that satisfies a wave equation. The continuous imaging of TEM can be accomplished using the imaging methods in seismic interpretation after the diffusion equation is transformed into a fictitious wave equation. The interpretation method based on the imaging of a fictitious wave field could be used as a fast 3D inversion method. Moreover, the fictitious wave field possesses some wave field features making it possible for the application of a wave field interpretation method in TEM to improve the prospecting resolution.Wave field transformation is a key issue in the migration imaging of a fictitious wave field. The equation in the wave field transformation belongs to the first class Fredholm integration equation, which is a typical ill-posed equation. Additionally, TEM has a large dynamic time range, which also facilitates the weakness of this ill-posed problem. The wave field transformation is implemented by using pre-conditioned regularized conjugate gradient method. The continuous imaging of a fictitious wave field is implemented by using Kirchhoff integration. A synthetic aperture and deconvolution algorithm is also introduced to improve the interpretation resolution. We interpreted field data by the method proposed in this paper, and obtained a satisfying interpretation result. (paper)

Aircraft target detection algorithm based on high resolution spaceborne SAR imagery

Science.gov (United States)

Zhang, Hui; Hao, Mengxi; Zhang, Cong; Su, Xiaojing

2018-03-01

In this paper, an image classification algorithm for airport area is proposed, which based on the statistical features of synthetic aperture radar (SAR) images and the spatial information of pixels. The algorithm combines Gamma mixture model and MRF. The algorithm using Gamma mixture model to obtain the initial classification result. Pixel space correlation based on the classification results are optimized by the MRF technique. Additionally, morphology methods are employed to extract airport (ROI) region where the suspected aircraft target samples are clarified to reduce the false alarm and increase the detection performance. Finally, this paper presents the plane target detection, which have been verified by simulation test.

DEM GENERATION FROM HIGH RESOLUTION SATELLITE IMAGES THROUGH A NEW 3D LEAST SQUARES MATCHING ALGORITHM

Directory of Open Access Journals (Sweden)

T. Kim

2012-09-01

Full Text Available Automated generation of digital elevation models (DEMs from high resolution satellite images (HRSIs has been an active research topic for many years. However, stereo matching of HRSIs, in particular based on image-space search, is still difficult due to occlusions and building facades within them. Object-space matching schemes, proposed to overcome these problem, often are very time consuming and critical to the dimensions of voxels. In this paper, we tried a new least square matching (LSM algorithm that works in a 3D object space. The algorithm starts with an initial height value on one location of the object space. From this 3D point, the left and right image points are projected. The true height is calculated by iterative least squares estimation based on the grey level differences between the left and right patches centred on the projected left and right points. We tested the 3D LSM to the Worldview images over 'Terrassa Sud' provided by the ISPRS WG I/4. We also compared the performance of the 3D LSM with the correlation matching based on 2D image space and the correlation matching based on 3D object space. The accuracy of the DEM from each method was analysed against the ground truth. Test results showed that 3D LSM offers more accurate DEMs over the conventional matching algorithms. Results also showed that 3D LSM is sensitive to the accuracy of initial height value to start the estimation. We combined the 3D COM and 3D LSM for accurate and robust DEM generation from HRSIs. The major contribution of this paper is that we proposed and validated that LSM can be applied to object space and that the combination of 3D correlation and 3D LSM can be a good solution for automated DEM generation from HRSIs.

A Fast DOA Estimation Algorithm Based on Polarization MUSIC

Directory of Open Access Journals (Sweden)

R. Guo

2015-04-01

Full Text Available A fast DOA estimation algorithm developed from MUSIC, which also benefits from the processing of the signals' polarization information, is presented. Besides performance enhancement in precision and resolution, the proposed algorithm can be exerted on various forms of polarization sensitive arrays, without specific requirement on the array's pattern. Depending on the continuity property of the space spectrum, a huge amount of computation incurred in the calculation of 4-D space spectrum is averted. Performance and computation complexity analysis of the proposed algorithm is discussed and the simulation results are presented. Compared with conventional MUSIC, it is indicated that the proposed algorithm has considerable advantage in aspects of precision and resolution, with a low computation complexity proportional to a conventional 2-D MUSIC.

A Denotational Account of Untyped Normalization by Evaluation

DEFF Research Database (Denmark)

Filinski, Andrzej; Rohde, Henning Korsholm

2004-01-01

We show that the standard normalization-by-evaluation construction for the simply-typed λβγ-calculus has a natural counterpart for the untyped λβ-calculus, with the central type-indexed logical relation replaced by a recursively defined invariant relation, in the style of Pitts. In fact, the cons...... proof for the normalization algorithm, expressed as a functional program in an ML-like call-by-value language. A version of this article with detailed proofs is available as a technical report [5]....

Resolution enhancement of tri-stereo remote sensing images by super resolution methods

Science.gov (United States)

Tuna, Caglayan; Akoguz, Alper; Unal, Gozde; Sertel, Elif

2016-10-01

Super resolution (SR) refers to generation of a High Resolution (HR) image from a decimated, blurred, low-resolution (LR) image set, which can be either a single frame or multi-frame that contains a collection of several images acquired from slightly different views of the same observation area. In this study, we propose a novel application of tri-stereo Remote Sensing (RS) satellite images to the super resolution problem. Since the tri-stereo RS images of the same observation area are acquired from three different viewing angles along the flight path of the satellite, these RS images are properly suited to a SR application. We first estimate registration between the chosen reference LR image and other LR images to calculate the sub pixel shifts among the LR images. Then, the warping, blurring and down sampling matrix operators are created as sparse matrices to avoid high memory and computational requirements, which would otherwise make the RS-SR solution impractical. Finally, the overall system matrix, which is constructed based on the obtained operator matrices is used to obtain the estimate HR image in one step in each iteration of the SR algorithm. Both the Laplacian and total variation regularizers are incorporated separately into our algorithm and the results are presented to demonstrate an improved quantitative performance against the standard interpolation method as well as improved qualitative results due expert evaluations.

An ML-Based Radial Velocity Estimation Algorithm for Moving Targets in Spaceborne High-Resolution and Wide-Swath SAR Systems

Directory of Open Access Journals (Sweden)

Tingting Jin

2017-04-01

Full Text Available Multichannel synthetic aperture radar (SAR is a significant breakthrough to the inherent limitation between high-resolution and wide-swath (HRWS compared with conventional SAR. Moving target indication (MTI is an important application of spaceborne HRWS SAR systems. In contrast to previous studies of SAR MTI, the HRWS SAR mainly faces the problem of under-sampled data of each channel, causing single-channel imaging and processing to be infeasible. In this study, the estimation of velocity is equivalent to the estimation of the cone angle according to their relationship. The maximum likelihood (ML based algorithm is proposed to estimate the radial velocity in the existence of Doppler ambiguities. After that, the signal reconstruction and compensation for the phase offset caused by radial velocity are processed for a moving target. Finally, the traditional imaging algorithm is applied to obtain a focused moving target image. Experiments are conducted to evaluate the accuracy and effectiveness of the estimator under different signal-to-noise ratios (SNR. Furthermore, the performance is analyzed with respect to the motion ship that experiences interference due to different distributions of sea clutter. The results verify that the proposed algorithm is accurate and efficient with low computational complexity. This paper aims at providing a solution to the velocity estimation problem in the future HRWS SAR systems with multiple receive channels.

Super-resolution in plenoptic cameras using FPGAs.

Science.gov (United States)

Pérez, Joel; Magdaleno, Eduardo; Pérez, Fernando; Rodríguez, Manuel; Hernández, David; Corrales, Jaime

2014-05-16

Plenoptic cameras are a new type of sensor that extend the possibilities of current commercial cameras allowing 3D refocusing or the capture of 3D depths. One of the limitations of plenoptic cameras is their limited spatial resolution. In this paper we describe a fast, specialized hardware implementation of a super-resolution algorithm for plenoptic cameras. The algorithm has been designed for field programmable graphic array (FPGA) devices using VHDL (very high speed integrated circuit (VHSIC) hardware description language). With this technology, we obtain an acceleration of several orders of magnitude using its extremely high-performance signal processing capability through parallelism and pipeline architecture. The system has been developed using generics of the VHDL language. This allows a very versatile and parameterizable system. The system user can easily modify parameters such as data width, number of microlenses of the plenoptic camera, their size and shape, and the super-resolution factor. The speed of the algorithm in FPGA has been successfully compared with the execution using a conventional computer for several image sizes and different 3D refocusing planes.

Super-Resolution in Plenoptic Cameras Using FPGAs

Directory of Open Access Journals (Sweden)

Joel Pérez

2014-05-01

Full Text Available Plenoptic cameras are a new type of sensor that extend the possibilities of current commercial cameras allowing 3D refocusing or the capture of 3D depths. One of the limitations of plenoptic cameras is their limited spatial resolution. In this paper we describe a fast, specialized hardware implementation of a super-resolution algorithm for plenoptic cameras. The algorithm has been designed for field programmable graphic array (FPGA devices using VHDL (very high speed integrated circuit (VHSIC hardware description language. With this technology, we obtain an acceleration of several orders of magnitude using its extremely high-performance signal processing capability through parallelism and pipeline architecture. The system has been developed using generics of the VHDL language. This allows a very versatile and parameterizable system. The system user can easily modify parameters such as data width, number of microlenses of the plenoptic camera, their size and shape, and the super-resolution factor. The speed of the algorithm in FPGA has been successfully compared with the execution using a conventional computer for several image sizes and different 3D refocusing planes.

SPECT imaging with resolution recovery

International Nuclear Information System (INIS)

Bronnikov, A. V.

2011-01-01

Single-photon emission computed tomography (SPECT) is a method of choice for imaging spatial distributions of radioisotopes. Many applications of this method are found in nuclear industry, medicine, and biomedical research. We study mathematical modeling of a micro-SPECT system by using a point-spread function (PSF) and implement an OSEM-based iterative algorithm for image reconstruction with resolution recovery. Unlike other known implementations of the OSEM algorithm, we apply en efficient computation scheme based on a useful approximation of the PSF, which ensures relatively fast computations. The proposed approach can be applied with the data acquired with any type of collimators, including parallel-beam fan-beam, cone-beam and pinhole collimators. Experimental results obtained with a micro SPECT system demonstrate high efficiency of resolution recovery. (authors)

Underwater video enhancement using multi-camera super-resolution

Science.gov (United States)

Quevedo, E.; Delory, E.; Callicó, G. M.; Tobajas, F.; Sarmiento, R.

2017-12-01

Image spatial resolution is critical in several fields such as medicine, communications or satellite, and underwater applications. While a large variety of techniques for image restoration and enhancement has been proposed in the literature, this paper focuses on a novel Super-Resolution fusion algorithm based on a Multi-Camera environment that permits to enhance the quality of underwater video sequences without significantly increasing computation. In order to compare the quality enhancement, two objective quality metrics have been used: PSNR (Peak Signal-to-Noise Ratio) and the SSIM (Structural SIMilarity) index. Results have shown that the proposed method enhances the objective quality of several underwater sequences, avoiding the appearance of undesirable artifacts, with respect to basic fusion Super-Resolution algorithms.

Identification of overlapping communities and their hierarchy by locally calculating community-changing resolution levels

International Nuclear Information System (INIS)

Havemann, Frank; Heinz, Michael; Struck, Alexander; Gläser, Jochen

2011-01-01

We propose a new local, deterministic and parameter-free algorithm that detects fuzzy and crisp overlapping communities in a weighted network and simultaneously reveals their hierarchy. Using a local fitness function, the algorithm greedily expands natural communities of seeds until the whole graph is covered. The hierarchy of communities is obtained analytically by calculating resolution levels at which communities grow rather than numerically by testing different resolution levels. This analytic procedure is not only more exact than its numerical alternatives such as LFM and GCE but also much faster. Critical resolution levels can be identified by searching for intervals in which large changes of the resolution do not lead to growth of communities. We tested our algorithm on benchmark graphs and on a network of 492 papers in information science. Combined with a specific post-processing, the algorithm gives much more precise results on LFR benchmarks with high overlap compared to other algorithms and performs very similarly to GCE

Identification of overlapping communities and their hierarchy by locally calculating community-changing resolution levels

Science.gov (United States)

Havemann, Frank; Heinz, Michael; Struck, Alexander; Gläser, Jochen

2011-01-01

We propose a new local, deterministic and parameter-free algorithm that detects fuzzy and crisp overlapping communities in a weighted network and simultaneously reveals their hierarchy. Using a local fitness function, the algorithm greedily expands natural communities of seeds until the whole graph is covered. The hierarchy of communities is obtained analytically by calculating resolution levels at which communities grow rather than numerically by testing different resolution levels. This analytic procedure is not only more exact than its numerical alternatives such as LFM and GCE but also much faster. Critical resolution levels can be identified by searching for intervals in which large changes of the resolution do not lead to growth of communities. We tested our algorithm on benchmark graphs and on a network of 492 papers in information science. Combined with a specific post-processing, the algorithm gives much more precise results on LFR benchmarks with high overlap compared to other algorithms and performs very similarly to GCE.

Automated Verification of Spatial Resolution in Remotely Sensed Imagery

Science.gov (United States)

Davis, Bruce; Ryan, Robert; Holekamp, Kara; Vaughn, Ronald

2011-01-01

Image spatial resolution characteristics can vary widely among sources. In the case of aerial-based imaging systems, the image spatial resolution characteristics can even vary between acquisitions. In these systems, aircraft altitude, speed, and sensor look angle all affect image spatial resolution. Image spatial resolution needs to be verified with estimators that include the ground sample distance (GSD), the modulation transfer function (MTF), and the relative edge response (RER), all of which are key components of image quality, along with signal-to-noise ratio (SNR) and dynamic range. Knowledge of spatial resolution parameters is important to determine if features of interest are distinguishable in imagery or associated products, and to develop image restoration algorithms. An automated Spatial Resolution Verification Tool (SRVT) was developed to rapidly determine the spatial resolution characteristics of remotely sensed aerial and satellite imagery. Most current methods for assessing spatial resolution characteristics of imagery rely on pre-deployed engineered targets and are performed only at selected times within preselected scenes. The SRVT addresses these insufficiencies by finding uniform, high-contrast edges from urban scenes and then using these edges to determine standard estimators of spatial resolution, such as the MTF and the RER. The SRVT was developed using the MATLAB programming language and environment. This automated software algorithm assesses every image in an acquired data set, using edges found within each image, and in many cases eliminating the need for dedicated edge targets. The SRVT automatically identifies high-contrast, uniform edges and calculates the MTF and RER of each image, and when possible, within sections of an image, so that the variation of spatial resolution characteristics across the image can be analyzed. The automated algorithm is capable of quickly verifying the spatial resolution quality of all images within a data

Super Resolution and Interference Suppression Technique applied to SHARAD Radar Data

Science.gov (United States)

Raguso, M. C.; Mastrogiuseppe, M.; Seu, R.; Piazzo, L.

2017-12-01

We will present a super resolution and interference suppression technique applied to the data acquired by the SHAllow RADar (SHARAD) on board the NASA's 2005 Mars Reconnaissance Orbiter (MRO) mission, currently operating around Mars [1]. The algorithms allow to improve the range resolution roughly by a factor of 3 and the Signal to Noise Ratio (SNR) by a several decibels. Range compression algorithms usually adopt conventional Fourier transform techniques, which are limited in the resolution by the transmitted signal bandwidth, analogous to the Rayleigh's criterion in optics. In this work, we investigate a super resolution method based on autoregressive models and linear prediction techniques [2]. Starting from the estimation of the linear prediction coefficients from the spectral data, the algorithm performs the radar bandwidth extrapolation (BWE), thereby improving the range resolution of the pulse-compressed coherent radar data. Moreover, the EMIs (ElectroMagnetic Interferences) are detected and the spectra is interpolated in order to reconstruct an interference free spectrum, thereby improving the SNR. The algorithm can be applied to the single complex look image after synthetic aperture processing (SAR). We apply the proposed algorithm to simulated as well as to real radar data. We will demonstrate the effective enhancement on vertical resolution with respect to the classical spectral estimator. We will show that the imaging of the subsurface layered structures observed in radargrams is improved, allowing additional insights for the scientific community in the interpretation of the SHARAD radar data, which will help to further our understanding of the formation and evolution of known geological features on Mars. References: [1] Seu et al. 2007, Science, 2007, 317, 1715-1718 [2] K.M. Cuomo, "A Bandwidth Extrapolation Technique for Improved Range Resolution of Coherent Radar Data", Project Report CJP-60, Revision 1, MIT Lincoln Laboratory (4 Dec. 1992).

Testing Snow Melt Algorithms in High Relief Topography Using Calibrated Enhanced-Resolution Brightness Temperatures, Hunza River Basin, Pakistan

Science.gov (United States)

Ramage, J. M.; Brodzik, M. J.; Hardman, M.; Troy, T. J.

2017-12-01

Snow is a vital part of the terrestrial hydrological cycle, a crucial resource for people and ecosystems. In mountainous regions snow is extensive, variable, and challenging to document. Snow melt timing and duration are important factors affecting the transfer of snow mass to soil moisture and runoff. Passive microwave brightness temperature (Tb) changes at 36 and 18 GHz are a sensitive way to detect snow melt onset due to their sensitivity to the abrupt change in emissivity. They are widely used on large icefields and high latitude watersheds. The coarse resolution ( 25 km) of historically available data has precluded effective use in high relief, heterogeneous regions, and gaps between swaths also create temporal data gaps at lower latitudes. New enhanced resolution data products generated from a scatterometer image reconstruction for radiometer (rSIR) technique are available at the original frequencies. We use these Calibrated Enhanced-resolution Brightness (CETB) Temperatures Earth System Data Records (ESDR) to evaluate existing snow melt detection algorithms that have been used in other environments, including the cross polarized gradient ratio (XPGR) and the diurnal amplitude variations (DAV) approaches. We use the 36/37 GHz (3.125 km resolution) and 18/19 GHz (6.25 km resolution) vertically and horizontally polarized datasets from the Special Sensor Microwave Imager (SSM/I) and Advanced Microwave Radiometer for EOS (AMSR-E) and evaluate them for use in this high relief environment. The new data are used to assess glacier and snow melt records in the Hunza River Basin [area 13,000 sq. km, located at 36N, 74E], a tributary to the Upper Indus Basin, Pakistan. We compare the melt timing results visually and quantitatively to the corresponding EASE-Grid 2.0 25-km dataset, SRTM topography, and surface temperatures from station and reanalysis data. The new dataset is coarser than the topography, but is able to differentiate signals of melt/refreeze timing for

Recursive algorithms for phylogenetic tree counting.

Science.gov (United States)

Gavryushkina, Alexandra; Welch, David; Drummond, Alexei J

2013-10-28

In Bayesian phylogenetic inference we are interested in distributions over a space of trees. The number of trees in a tree space is an important characteristic of the space and is useful for specifying prior distributions. When all samples come from the same time point and no prior information available on divergence times, the tree counting problem is easy. However, when fossil evidence is used in the inference to constrain the tree or data are sampled serially, new tree spaces arise and counting the number of trees is more difficult. We describe an algorithm that is polynomial in the number of sampled individuals for counting of resolutions of a constraint tree assuming that the number of constraints is fixed. We generalise this algorithm to counting resolutions of a fully ranked constraint tree. We describe a quadratic algorithm for counting the number of possible fully ranked trees on n sampled individuals. We introduce a new type of tree, called a fully ranked tree with sampled ancestors, and describe a cubic time algorithm for counting the number of such trees on n sampled individuals. These algorithms should be employed for Bayesian Markov chain Monte Carlo inference when fossil data are included or data are serially sampled.

Multi-example feature-constrained back-projection method for image super-resolution

Institute of Scientific and Technical Information of China (English)

Junlei Zhang; Dianguang Gai; Xin Zhang; Xuemei Li

2017-01-01

Example-based super-resolution algorithms,which predict unknown high-resolution image information using a relationship model learnt from known high- and low-resolution image pairs, have attracted considerable interest in the field of image processing. In this paper, we propose a multi-example feature-constrained back-projection method for image super-resolution. Firstly, we take advantage of a feature-constrained polynomial interpolation method to enlarge the low-resolution image. Next, we consider low-frequency images of different resolutions to provide an example pair. Then, we use adaptive k NN search to find similar patches in the low-resolution image for every image patch in the high-resolution low-frequency image, leading to a regression model between similar patches to be learnt. The learnt model is applied to the low-resolution high-frequency image to produce high-resolution high-frequency information. An iterative back-projection algorithm is used as the final step to determine the final high-resolution image.Experimental results demonstrate that our method improves the visual quality of the high-resolution image.

Iterative Nonlinear Tikhonov Algorithm with Constraints for Electromagnetic Tomography

Science.gov (United States)

Xu, Feng; Deshpande, Manohar

2012-01-01

Low frequency electromagnetic tomography such as the capacitance tomography (ECT) has been proposed for monitoring and mass-gauging of gas-liquid two-phase system under microgravity condition in NASA's future long-term space missions. Due to the ill-posed inverse problem of ECT, images reconstructed using conventional linear algorithms often suffer from limitations such as low resolution and blurred edges. Hence, new efficient high resolution nonlinear imaging algorithms are needed for accurate two-phase imaging. The proposed Iterative Nonlinear Tikhonov Regularized Algorithm with Constraints (INTAC) is based on an efficient finite element method (FEM) forward model of quasi-static electromagnetic problem. It iteratively minimizes the discrepancy between FEM simulated and actual measured capacitances by adjusting the reconstructed image using the Tikhonov regularized method. More importantly, it enforces the known permittivity of two phases to the unknown pixels which exceed the reasonable range of permittivity in each iteration. This strategy does not only stabilize the converging process, but also produces sharper images. Simulations show that resolution improvement of over 2 times can be achieved by INTAC with respect to conventional approaches. Strategies to further improve spatial imaging resolution are suggested, as well as techniques to accelerate nonlinear forward model and thus increase the temporal resolution.

Interior tomography in microscopic CT with image reconstruction constrained by full field of view scan at low spatial resolution

Science.gov (United States)

Luo, Shouhua; Shen, Tao; Sun, Yi; Li, Jing; Li, Guang; Tang, Xiangyang

2018-04-01

In high resolution (microscopic) CT applications, the scan field of view should cover the entire specimen or sample to allow complete data acquisition and image reconstruction. However, truncation may occur in projection data and results in artifacts in reconstructed images. In this study, we propose a low resolution image constrained reconstruction algorithm (LRICR) for interior tomography in microscopic CT at high resolution. In general, the multi-resolution acquisition based methods can be employed to solve the data truncation problem if the project data acquired at low resolution are utilized to fill up the truncated projection data acquired at high resolution. However, most existing methods place quite strict restrictions on the data acquisition geometry, which greatly limits their utility in practice. In the proposed LRICR algorithm, full and partial data acquisition (scan) at low and high resolutions, respectively, are carried out. Using the image reconstructed from sparse projection data acquired at low resolution as the prior, a microscopic image at high resolution is reconstructed from the truncated projection data acquired at high resolution. Two synthesized digital phantoms, a raw bamboo culm and a specimen of mouse femur, were utilized to evaluate and verify performance of the proposed LRICR algorithm. Compared with the conventional TV minimization based algorithm and the multi-resolution scout-reconstruction algorithm, the proposed LRICR algorithm shows significant improvement in reduction of the artifacts caused by data truncation, providing a practical solution for high quality and reliable interior tomography in microscopic CT applications. The proposed LRICR algorithm outperforms the multi-resolution scout-reconstruction method and the TV minimization based reconstruction for interior tomography in microscopic CT.

Resolution Enhancement Algorithm for Spaceborn SAR Based on Hanning Function Weighted Sidelobe Suppression

Science.gov (United States)

Li, C.; Zhou, X.; Tang, D.; Zhu, Z.

2018-04-01

Resolution and sidelobe are mutual restrict for SAR image. Usually sidelobe suppression is based on resolution reduction. This paper provide a method for resolution enchancement using sidelobe opposition speciality of hanning window and SAR image. The method can keep high resolution on the condition of sidelobe suppression. Compare to traditional method, this method can enchance 50 % resolution when sidelobe is -30dB.

Study on a digital pulse processing algorithm based on template-matching for high-throughput spectroscopy

Energy Technology Data Exchange (ETDEWEB)

Wen, Xianfei; Yang, Haori

2015-06-01

A major challenge in utilizing spectroscopy techniques for nuclear safeguards is to perform high-resolution measurements at an ultra-high throughput rate. Traditionally, piled-up pulses are rejected to ensure good energy resolution. To improve throughput rate, high-pass filters are normally implemented to shorten pulses. However, this reduces signal-to-noise ratio and causes degradation in energy resolution. In this work, a pulse pile-up recovery algorithm based on template-matching was proved to be an effective approach to achieve high-throughput gamma ray spectroscopy. First, a discussion of the algorithm was given in detail. Second, the algorithm was then successfully utilized to process simulated piled-up pulses from a scintillator detector. Third, the algorithm was implemented to analyze high rate data from a NaI detector, a silicon drift detector and a HPGe detector. The promising results demonstrated the capability of this algorithm to achieve high-throughput rate without significant sacrifice in energy resolution. The performance of the template-matching algorithm was also compared with traditional shaping methods. - Highlights: • A detailed discussion on the template-matching algorithm was given. • The algorithm was tested on data from a NaI and a Si detector. • The algorithm was successfully implemented on high rate data from a HPGe detector. • The performance of the algorithm was compared with traditional shaping methods. • The advantage of the algorithm in active interrogation was discussed.

Combining a Deconvolution and a Universal Library Search Algorithm for the Nontarget Analysis of Data-Independent Acquisition Mode Liquid Chromatography-High-Resolution Mass Spectrometry Results.

Science.gov (United States)

Samanipour, Saer; Reid, Malcolm J; Bæk, Kine; Thomas, Kevin V

2018-04-17

Nontarget analysis is considered one of the most comprehensive tools for the identification of unknown compounds in a complex sample analyzed via liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS). Due to the complexity of the data generated via LC-HRMS, the data-dependent acquisition mode, which produces the MS 2 spectra of a limited number of the precursor ions, has been one of the most common approaches used during nontarget screening. However, data-independent acquisition mode produces highly complex spectra that require proper deconvolution and library search algorithms. We have developed a deconvolution algorithm and a universal library search algorithm (ULSA) for the analysis of complex spectra generated via data-independent acquisition. These algorithms were validated and tested using both semisynthetic and real environmental data. A total of 6000 randomly selected spectra from MassBank were introduced across the total ion chromatograms of 15 sludge extracts at three levels of background complexity for the validation of the algorithms via semisynthetic data. The deconvolution algorithm successfully extracted more than 60% of the added ions in the analytical signal for 95% of processed spectra (i.e., 3 complexity levels multiplied by 6000 spectra). The ULSA ranked the correct spectra among the top three for more than 95% of cases. We further tested the algorithms with 5 wastewater effluent extracts for 59 artificial unknown analytes (i.e., their presence or absence was confirmed via target analysis). These algorithms did not produce any cases of false identifications while correctly identifying ∼70% of the total inquiries. The implications, capabilities, and the limitations of both algorithms are further discussed.

Effective noise-suppressed and artifact-reduced reconstruction of SPECT data using a preconditioned alternating projection algorithm

Energy Technology Data Exchange (ETDEWEB)

Li, Si; Xu, Yuesheng, E-mail: yxu06@syr.edu [Guangdong Provincial Key Laboratory of Computational Science, School of Mathematics and Computational Sciences, Sun Yat-sen University, Guangzhou 510275 (China); Zhang, Jiahan; Lipson, Edward [Department of Physics, Syracuse University, Syracuse, New York 13244 (United States); Krol, Andrzej; Feiglin, David [Department of Radiology, SUNY Upstate Medical University, Syracuse, New York 13210 (United States); Schmidtlein, C. Ross [Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York 10065 (United States); Vogelsang, Levon [Carestream Health, Rochester, New York 14608 (United States); Shen, Lixin [Guangdong Provincial Key Laboratory of Computational Science, School of Mathematics and Computational Sciences, Sun Yat-sen University, Guangzhou 510275, China and Department of Mathematics, Syracuse University, Syracuse, New York 13244 (United States)

2015-08-15

Purpose: The authors have recently developed a preconditioned alternating projection algorithm (PAPA) with total variation (TV) regularizer for solving the penalized-likelihood optimization model for single-photon emission computed tomography (SPECT) reconstruction. This algorithm belongs to a novel class of fixed-point proximity methods. The goal of this work is to investigate how PAPA performs while dealing with realistic noisy SPECT data, to compare its performance with more conventional methods, and to address issues with TV artifacts by proposing a novel form of the algorithm invoking high-order TV regularization, denoted as HOTV-PAPA, which has been explored and studied extensively in the present work. Methods: Using Monte Carlo methods, the authors simulate noisy SPECT data from two water cylinders; one contains lumpy “warm” background and “hot” lesions of various sizes with Gaussian activity distribution, and the other is a reference cylinder without hot lesions. The authors study the performance of HOTV-PAPA and compare it with PAPA using first-order TV regularization (TV-PAPA), the Panin–Zeng–Gullberg one-step-late method with TV regularization (TV-OSL), and an expectation–maximization algorithm with Gaussian postfilter (GPF-EM). The authors select penalty-weights (hyperparameters) by qualitatively balancing the trade-off between resolution and image noise separately for TV-PAPA and TV-OSL. However, the authors arrived at the same penalty-weight value for both of them. The authors set the first penalty-weight in HOTV-PAPA equal to the optimal penalty-weight found for TV-PAPA. The second penalty-weight needed for HOTV-PAPA is tuned by balancing resolution and the severity of staircase artifacts. The authors adjust the Gaussian postfilter to approximately match the local point spread function of GPF-EM and HOTV-PAPA. The authors examine hot lesion detectability, study local spatial resolution, analyze background noise properties, estimate mean

Effective noise-suppressed and artifact-reduced reconstruction of SPECT data using a preconditioned alternating projection algorithm

International Nuclear Information System (INIS)

Li, Si; Xu, Yuesheng; Zhang, Jiahan; Lipson, Edward; Krol, Andrzej; Feiglin, David; Schmidtlein, C. Ross; Vogelsang, Levon; Shen, Lixin

2015-01-01

Purpose: The authors have recently developed a preconditioned alternating projection algorithm (PAPA) with total variation (TV) regularizer for solving the penalized-likelihood optimization model for single-photon emission computed tomography (SPECT) reconstruction. This algorithm belongs to a novel class of fixed-point proximity methods. The goal of this work is to investigate how PAPA performs while dealing with realistic noisy SPECT data, to compare its performance with more conventional methods, and to address issues with TV artifacts by proposing a novel form of the algorithm invoking high-order TV regularization, denoted as HOTV-PAPA, which has been explored and studied extensively in the present work. Methods: Using Monte Carlo methods, the authors simulate noisy SPECT data from two water cylinders; one contains lumpy “warm” background and “hot” lesions of various sizes with Gaussian activity distribution, and the other is a reference cylinder without hot lesions. The authors study the performance of HOTV-PAPA and compare it with PAPA using first-order TV regularization (TV-PAPA), the Panin–Zeng–Gullberg one-step-late method with TV regularization (TV-OSL), and an expectation–maximization algorithm with Gaussian postfilter (GPF-EM). The authors select penalty-weights (hyperparameters) by qualitatively balancing the trade-off between resolution and image noise separately for TV-PAPA and TV-OSL. However, the authors arrived at the same penalty-weight value for both of them. The authors set the first penalty-weight in HOTV-PAPA equal to the optimal penalty-weight found for TV-PAPA. The second penalty-weight needed for HOTV-PAPA is tuned by balancing resolution and the severity of staircase artifacts. The authors adjust the Gaussian postfilter to approximately match the local point spread function of GPF-EM and HOTV-PAPA. The authors examine hot lesion detectability, study local spatial resolution, analyze background noise properties, estimate mean

RESOLUTION ENHANCEMENT ALGORITHM FOR SPACEBORN SAR BASED ON HANNING FUNCTION WEIGHTED SIDELOBE SUPPRESSION

Directory of Open Access Journals (Sweden)

C. Li

2018-04-01

Full Text Available Resolution and sidelobe are mutual restrict for SAR image. Usually sidelobe suppression is based on resolution reduction. This paper provide a method for resolution enchancement using sidelobe opposition speciality of hanning window and SAR image. The method can keep high resolution on the condition of sidelobe suppression. Compare to traditional method, this method can enchance 50 % resolution when sidelobe is −30dB.

A Fuel-Efficient Conflict Resolution Maneuver for Separation Assurance

Science.gov (United States)

Bowe, Aisha Ruth; Santiago, Confesor

2012-01-01

Automated separation assurance algorithms are envisioned to play an integral role in accommodating the forecasted increase in demand of the National Airspace System. Developing a robust, reliable, air traffic management system involves safely increasing efficiency and throughput while considering the potential impact on users. This experiment seeks to evaluate the benefit of augmenting a conflict detection and resolution algorithm to consider a fuel efficient, Zero-Delay Direct-To maneuver, when resolving a given conflict based on either minimum fuel burn or minimum delay. A total of twelve conditions were tested in a fast-time simulation conducted in three airspace regions with mixed aircraft types and light weather. Results show that inclusion of this maneuver has no appreciable effect on the ability of the algorithm to safely detect and resolve conflicts. The results further suggest that enabling the Zero-Delay Direct-To maneuver significantly increases the cumulative fuel burn savings when choosing resolution based on minimum fuel burn while marginally increasing the average delay per resolution.

SINGLE FRAME SUPER RESOLUTION OF NONCOOPERATIVE IRIS IMAGES

Directory of Open Access Journals (Sweden)

Anand Deshpande

2016-11-01

Full Text Available Image super-resolution, a process to enhance image resolution, has important applications in biometrics, satellite imaging, high definition television, medical imaging, etc. The long range captured iris identification systems often suffer from low resolution and meager focus of the captured iris images. These degrade the iris recognition performance. This paper proposes enhanced iterated back projection (EIBP method to super resolute the long range captured iris polar images. The performance of proposed method is tested and analyzed on CASIA long range iris database by comparing peak signal to noise ratio (PSNR and structural similarity index (SSIM with state-of-the-art super resolution (SR algorithms. It is further analyzed by increasing the up-sampling factor. Performance analysis shows that the proposed method is superior to state-of-the-art algorithms, the peak signal-to-noise ratio improved about 0.1-1.5 dB. The results demonstrate that the proposed method is well suited to super resolve the iris polar images captured at a long distance

Fast generation of multiple resolution instances of raster data sets

NARCIS (Netherlands)

Arge, L.; Haverkort, H.J.; Tsirogiannis, C.P.

2012-01-01

In many GIS applications it is important to study the characteristics of a raster data set at multiple resolutions. Often this is done by generating several coarser resolution rasters from a fine resolution raster. In this paper we describe efficient algorithms for different variants of this

A simple calculation algorithm to separate high-resolution CH4 flux measurements into ebullition and diffusion-derived components

Science.gov (United States)

Hoffmann, Mathias; Schulz-Hanke, Maximilian; Garcia Alba, Joana; Jurisch, Nicole; Hagemann, Ulrike; Sachs, Torsten; Sommer, Michael; Augustin, Jürgen

2016-04-01

Processes driving methane (CH4) emissions in wetland ecosystems are highly complex. Especially, the separation of CH4 emissions into ebullition and diffusion derived flux components, a perquisite for the mechanistic process understanding and identification of potential environmental driver is rather challenging. We present a simple calculation algorithm, based on an adaptive R-script, which separates open-water, closed chamber CH4 flux measurements into diffusion- and ebullition-derived components. Hence, flux component specific dynamics are revealed and potential environmental driver identified. Flux separation is based on a statistical approach, using ebullition related sudden concentration changes obtained during high resolution CH4 concentration measurements. By applying the lower and upper quartile ± the interquartile range (IQR) as a variable threshold, diffusion dominated periods of the flux measurement are filtered. Subsequently, flux calculation and separation is performed. The algorithm was verified in a laboratory experiment and tested under field conditions, using flux measurement data (July to September 2013) from a flooded, former fen grassland site. Erratic ebullition events contributed 46% to total CH4 emissions, which is comparable to values reported by literature. Additionally, a shift in the diurnal trend of diffusive fluxes throughout the measurement period, driven by the water temperature gradient, was revealed.

Multiangle Implementation of Atmospheric Correction (MAIAC): 2. Aerosol Algorithm

Science.gov (United States)

Lyapustin, A.; Wang, Y.; Laszlo, I.; Kahn, R.; Korkin, S.; Remer, L.; Levy, R.; Reid, J. S.

2011-01-01

An aerosol component of a new multiangle implementation of atmospheric correction (MAIAC) algorithm is presented. MAIAC is a generic algorithm developed for the Moderate Resolution Imaging Spectroradiometer (MODIS), which performs aerosol retrievals and atmospheric correction over both dark vegetated surfaces and bright deserts based on a time series analysis and image-based processing. The MAIAC look-up tables explicitly include surface bidirectional reflectance. The aerosol algorithm derives the spectral regression coefficient (SRC) relating surface bidirectional reflectance in the blue (0.47 micron) and shortwave infrared (2.1 micron) bands; this quantity is prescribed in the MODIS operational Dark Target algorithm based on a parameterized formula. The MAIAC aerosol products include aerosol optical thickness and a fine-mode fraction at resolution of 1 km. This high resolution, required in many applications such as air quality, brings new information about aerosol sources and, potentially, their strength. AERONET validation shows that the MAIAC and MOD04 algorithms have similar accuracy over dark and vegetated surfaces and that MAIAC generally improves accuracy over brighter surfaces due to the SRC retrieval and explicit bidirectional reflectance factor characterization, as demonstrated for several U.S. West Coast AERONET sites. Due to its generic nature and developed angular correction, MAIAC performs aerosol retrievals over bright deserts, as demonstrated for the Solar Village Aerosol Robotic Network (AERONET) site in Saudi Arabia.

A novel structure-aware sparse learning algorithm for brain imaging genetics.

Science.gov (United States)

Du, Lei; Jingwen, Yan; Kim, Sungeun; Risacher, Shannon L; Huang, Heng; Inlow, Mark; Moore, Jason H; Saykin, Andrew J; Shen, Li

2014-01-01

Brain imaging genetics is an emergent research field where the association between genetic variations such as single nucleotide polymorphisms (SNPs) and neuroimaging quantitative traits (QTs) is evaluated. Sparse canonical correlation analysis (SCCA) is a bi-multivariate analysis method that has the potential to reveal complex multi-SNP-multi-QT associations. Most existing SCCA algorithms are designed using the soft threshold strategy, which assumes that the features in the data are independent from each other. This independence assumption usually does not hold in imaging genetic data, and thus inevitably limits the capability of yielding optimal solutions. We propose a novel structure-aware SCCA (denoted as S2CCA) algorithm to not only eliminate the independence assumption for the input data, but also incorporate group-like structure in the model. Empirical comparison with a widely used SCCA implementation, on both simulated and real imaging genetic data, demonstrated that S2CCA could yield improved prediction performance and biologically meaningful findings.

A study of spatial resolution in pollution exposure modelling

Directory of Open Access Journals (Sweden)

Gustafsson Susanna

2007-06-01

Full Text Available Abstract Background This study is part of several ongoing projects concerning epidemiological research into the effects on health of exposure to air pollutants in the region of Scania, southern Sweden. The aim is to investigate the optimal spatial resolution, with respect to temporal resolution, for a pollutant database of NOx-values which will be used mainly for epidemiological studies with durations of days, weeks or longer periods. The fact that a pollutant database has a fixed spatial resolution makes the choice critical for the future use of the database. Results The results from the study showed that the accuracy between the modelled concentrations of the reference grid with high spatial resolution (100 m, denoted the fine grid, and the coarser grids (200, 400, 800 and 1600 meters improved with increasing spatial resolution. When the pollutant values were aggregated in time (from hours to days and weeks the disagreement between the fine grid and the coarser grids were significantly reduced. The results also illustrate a considerable difference in optimal spatial resolution depending on the characteristic of the study area (rural or urban areas. To estimate the accuracy of the modelled values comparison were made with measured NOx values. The mean difference between the modelled and the measured value were 0.6 μg/m3 and the standard deviation 5.9 μg/m3 for the daily difference. Conclusion The choice of spatial resolution should not considerably deteriorate the accuracy of the modelled NOx values. Considering the comparison between modelled and measured values we estimate that an error due to coarse resolution greater than 1 μg/m3 is inadvisable if a time resolution of one day is used. Based on the study of different spatial resolutions we conclude that for urban areas a spatial resolution of 200–400 m is suitable; and for rural areas the spatial resolution could be coarser (about 1600 m. This implies that we should develop a pollutant

A Taxonomy for Modeling Flexibility and a Computationally Efficient Algorithm for Dispatch in Smart Grids

DEFF Research Database (Denmark)

Petersen, Mette Højgaard; Edlund, Kristian; Hansen, Lars Henrik

2013-01-01

The word flexibility is central to Smart Grid literature, but still a formal definition of flexibility is pending. This paper present a taxonomy for flexibility modeling denoted Buckets, Batteries and Bakeries. We consider a direct control Virtual Power Plant (VPP), which is given the task...... of servicing a portfolio of flexible consumers by use of a fluctuating power supply. Based on the developed taxonomy we first prove that no causal optimal dispatch strategies exist for the considered problem. We then present two heuristic algorithms for solving the balancing task: Predictive Balancing...

I/O-Optimal Distribution Sweeping on Private-Cache Chip Multiprocessors

DEFF Research Database (Denmark)

Ajwani, Deepak; Sitchinava, Nodar; Zeh, Norbert

2011-01-01

/PB) for a number of problems on axis aligned objects; P denotes the number of cores/processors, B denotes the number of elements that fit in a cache line, N and K denote the sizes of the input and output, respectively, and sortp(N) denotes the I/O complexity of sorting N items using P processors in the PEM model...... framework was introduced recently, and a number of algorithms for problems on axis-aligned objects were obtained using this framework. The obtained algorithms were efficient but not optimal. In this paper, we improve the framework to obtain algorithms with the optimal I/O complexity of O(sortp(N) + K...

Generic Entity Resolution in Relational Databases

Science.gov (United States)

Sidló, Csaba István

Entity Resolution (ER) covers the problem of identifying distinct representations of real-world entities in heterogeneous databases. We consider the generic formulation of ER problems (GER) with exact outcome. In practice, input data usually resides in relational databases and can grow to huge volumes. Yet, typical solutions described in the literature employ standalone memory resident algorithms. In this paper we utilize facilities of standard, unmodified relational database management systems (RDBMS) to enhance the efficiency of GER algorithms. We study and revise the problem formulation, and propose practical and efficient algorithms optimized for RDBMS external memory processing. We outline a real-world scenario and demonstrate the advantage of algorithms by performing experiments on insurance customer data.

EUV lithography for 30nm half pitch and beyond: exploring resolution, sensitivity, and LWR tradeoffs

Science.gov (United States)

Putna, E. Steve; Younkin, Todd R.; Chandhok, Manish; Frasure, Kent

2009-03-01

The International Technology Roadmap for Semiconductors (ITRS) denotes Extreme Ultraviolet (EUV) lithography as a leading technology option for realizing the 32nm half-pitch node and beyond. Readiness of EUV materials is currently one high risk area according to assessments made at the 2008 EUVL Symposium. The main development issue regarding EUV resist has been how to simultaneously achieve high sensitivity, high resolution, and low line width roughness (LWR). This paper describes the strategy and current status of EUV resist development at Intel Corporation. Data is presented utilizing Intel's Micro-Exposure Tool (MET) examining the feasibility of establishing a resist process that simultaneously exhibits <=30nm half-pitch (HP) L/S resolution at <=10mJ/cm2 with <=4nm LWR.

An interactive, web-based tool for genealogical entity resolution

NARCIS (Netherlands)

Efremova, I.; Ranjbar-Sahraei, B.; Oliehoek, F.A.; Calders, T.G.K.; Tuyls, K.P.

2013-01-01

We demonstrate an interactive, web-based tool which helps historians to do Genealogical Entitiy Resolution. This work has two main goals. First, it uses Machine Learning (ML) algorithms to assist humanites researchers to perform Genealogical Entity Resolution. Second, it facilitates the generation

An efficient community detection algorithm using greedy surprise maximization

International Nuclear Information System (INIS)

Jiang, Yawen; Jia, Caiyan; Yu, Jian

2014-01-01

Community detection is an important and crucial problem in complex network analysis. Although classical modularity function optimization approaches are widely used for identifying communities, the modularity function (Q) suffers from its resolution limit. Recently, the surprise function (S) was experimentally proved to be better than the Q function. However, up until now, there has been no algorithm available to perform searches to directly determine the maximal surprise values. In this paper, considering the superiority of the S function over the Q function, we propose an efficient community detection algorithm called AGSO (algorithm based on greedy surprise optimization) and its improved version FAGSO (fast-AGSO), which are based on greedy surprise optimization and do not suffer from the resolution limit. In addition, (F)AGSO does not need the number of communities K to be specified in advance. Tests on experimental networks show that (F)AGSO is able to detect optimal partitions in both simple and even more complex networks. Moreover, algorithms based on surprise maximization perform better than those algorithms based on modularity maximization, including Blondel–Guillaume–Lambiotte–Lefebvre (BGLL), Clauset–Newman–Moore (CNM) and the other state-of-the-art algorithms such as Infomap, order statistics local optimization method (OSLOM) and label propagation algorithm (LPA). (paper)

A nonlinear filtering algorithm for denoising HR(S)TEM micrographs

International Nuclear Information System (INIS)

Du, Hongchu

2015-01-01

Noise reduction of micrographs is often an essential task in high resolution (scanning) transmission electron microscopy (HR(S)TEM) either for a higher visual quality or for a more accurate quantification. Since HR(S)TEM studies are often aimed at resolving periodic atomistic columns and their non-periodic deviation at defects, it is important to develop a noise reduction algorithm that can simultaneously handle both periodic and non-periodic features properly. In this work, a nonlinear filtering algorithm is developed based on widely used techniques of low-pass filter and Wiener filter, which can efficiently reduce noise without noticeable artifacts even in HR(S)TEM micrographs with contrast of variation of background and defects. The developed nonlinear filtering algorithm is particularly suitable for quantitative electron microscopy, and is also of great interest for beam sensitive samples, in situ analyses, and atomic resolution EFTEM. - Highlights: • A nonlinear filtering algorithm for denoising HR(S)TEM images is developed. • It can simultaneously handle both periodic and non-periodic features properly. • It is particularly suitable for quantitative electron microscopy. • It is of great interest for beam sensitive samples, in situ analyses, and atomic resolution EFTEM

Optimisation of centroiding algorithms for photon event counting imaging

International Nuclear Information System (INIS)

Suhling, K.; Airey, R.W.; Morgan, B.L.

1999-01-01

Approaches to photon event counting imaging in which the output events of an image intensifier are located using a centroiding technique have long been plagued by fixed pattern noise in which a grid of dimensions similar to those of the CCD pixels is superimposed on the image. This is caused by a mismatch between the photon event shape and the centroiding algorithm. We have used hyperbolic cosine, Gaussian, Lorentzian, parabolic as well as 3-, 5-, and 7-point centre of gravity algorithms, and hybrids thereof, to assess means of minimising this fixed pattern noise. We show that fixed pattern noise generated by the widely used centre of gravity centroiding is due to intrinsic features of the algorithm. Our results confirm that the recently proposed use of Gaussian centroiding does indeed show a significant reduction of fixed pattern noise compared to centre of gravity centroiding (Michel et al., Mon. Not. R. Astron. Soc. 292 (1997) 611-620). However, the disadvantage of a Gaussian algorithm is a centroiding failure for small pulses, caused by a division by zero, which leads to a loss of detective quantum efficiency (DQE) and to small amounts of residual fixed pattern noise. Using both real data from an image intensifier system employing a progressive scan camera, framegrabber and PC, and also synthetic data from Monte-Carlo simulations, we find that hybrid centroiding algorithms can reduce the fixed pattern noise without loss of resolution or loss of DQE. Imaging a test pattern to assess the features of the different algorithms shows that a hybrid of Gaussian and 3-point centre of gravity centroiding algorithms results in an optimum combination of low fixed pattern noise (lower than a simple Gaussian), high DQE, and high resolution. The Lorentzian algorithm gives the worst results in terms of high fixed pattern noise and low resolution, and the Gaussian and hyperbolic cosine algorithms have the lowest DQEs

Resolution effects on the morphology of calcifications in digital mammograms

Energy Technology Data Exchange (ETDEWEB)

Kallergi, Maria; He, Li; Gavrielides, Marios; Heine, John; Clarke, Laurence P [Department of Radiology, College of Medicine, and H. Lee Moffitt Cancer Center and Research Institute at the University of South Florida, 12901 Bruce B. Downs Blvd., Box 17, Tampa, FL 33612 (United States)

1999-12-31

The development of computer assisted diagnosis (CAD) techniques and direct digital mammography systems have generated significant interest in the issue of the effect of image resolution on the detection and classification (benign vs malignant) of mammographic abnormalities. CAD in particular seems to heavily depend on image resolution, either due to the inherent algorithm design and optimization, which is almost always dependent, or due to the differences in image content at the various resolutions. This twofold dependence makes it even more difficult to answer the question of what is the minimum resolution required for successful detection and/or classification of a specific mammographic abnormality, such as calcifications. One may begin by evaluating the losses in the mammograms as the films are digitized with different pixel sizes and depths. In this paper we attempted to measure these losses for the case of calcifications at four different spatial resolutions through a simulation model and a classification scheme that is based only on morphological features. The results showed that a 60 {mu}m pixel size and 12 bits per pixel should at least be used if the morphology and distribution of the calcifications are essential components in the CAD algorithm design. These conclusions were tested with the use of a wavelet-based algorithm for the segmentation of simulated mammographic calcifications at various resolutions. The evaluation of the segmentation through shape analysis and classification supported the initial conclusion. (authors) 14 refs., 1 tabs.

Reducing Earth Topography Resolution for SMAP Mission Ground Tracks Using K-Means Clustering

Science.gov (United States)

Rizvi, Farheen

2013-01-01

The K-means clustering algorithm is used to reduce Earth topography resolution for the SMAP mission ground tracks. As SMAP propagates in orbit, knowledge of the radar antenna footprints on Earth is required for the antenna misalignment calibration. Each antenna footprint contains a latitude and longitude location pair on the Earth surface. There are 400 pairs in one data set for the calibration model. It is computationally expensive to calculate corresponding Earth elevation for these data pairs. Thus, the antenna footprint resolution is reduced. Similar topographical data pairs are grouped together with the K-means clustering algorithm. The resolution is reduced to the mean of each topographical cluster called the cluster centroid. The corresponding Earth elevation for each cluster centroid is assigned to the entire group. Results show that 400 data points are reduced to 60 while still maintaining algorithm performance and computational efficiency. In this work, sensitivity analysis is also performed to show a trade-off between algorithm performance versus computational efficiency as the number of cluster centroids and algorithm iterations are increased.

Wavelet-LMS algorithm-based echo cancellers

Science.gov (United States)

Seetharaman, Lalith K.; Rao, Sathyanarayana S.

2002-12-01

This paper presents Echo Cancellers based on the Wavelet-LMS Algorithm. The performance of the Least Mean Square Algorithm in Wavelet transform domain is observed and its application in Echo cancellation is analyzed. The Widrow-Hoff Least Mean Square Algorithm is most widely used algorithm for Adaptive filters that function as Echo Cancellers. The present day communication signals are widely non-stationary in nature and some errors crop up when Least Mean Square Algorithm is used for the Echo Cancellers handling such signals. The analysis of non-stationary signals often involves a compromise between how well transitions or discontinuities can be located. The multi-scale or multi-resolution of signal analysis, which is the essence of wavelet transform, makes Wavelets popular in non-stationary signal analysis. In this paper, we present a Wavelet-LMS algorithm wherein the wavelet coefficients of a signal are modified adaptively using the Least Mean Square Algorithm and then reconstructed to give an Echo-free signal. The Echo Canceller based on this Algorithm is found to have a better convergence and a comparatively lesser MSE (Mean Square error).

A new cut-based algorithm for the multi-state flow network reliability problem

International Nuclear Information System (INIS)

Yeh, Wei-Chang; Bae, Changseok; Huang, Chia-Ling

2015-01-01

Many real-world systems can be modeled as multi-state network systems in which reliability can be derived in terms of the lower bound points of level d, called d-minimal cuts (d-MCs). This study proposes a new method to find and verify obtained d-MCs with simple and useful found properties for the multi-state flow network reliability problem. The proposed algorithm runs in O(mσp) time, which represents a significant improvement over the previous O(mp 2 σ) time bound based on max-flow/min-cut, where p, σ and m denote the number of MCs, d-MC candidates and edges, respectively. The proposed algorithm also conquers the weakness of some existing methods, which failed to remove duplicate d-MCs in special cases. A step-by-step example is given to demonstrate how the proposed algorithm locates and verifies all d-MC candidates. As evidence of the utility of the proposed approach, we present extensive computational results on 20 benchmark networks in another example. The computational results compare favorably with a previously developed algorithm in the literature. - Highlights: • A new method is proposed to find all d-MCs for the multi-state flow networks. • The proposed method can prevent the generation of d-MC duplicates. • The proposed method is simpler and more efficient than the best-known algorithms

High-resolution coded-aperture design for compressive X-ray tomography using low resolution detectors

Science.gov (United States)

Mojica, Edson; Pertuz, Said; Arguello, Henry

2017-12-01

One of the main challenges in Computed Tomography (CT) is obtaining accurate reconstructions of the imaged object while keeping a low radiation dose in the acquisition process. In order to solve this problem, several researchers have proposed the use of compressed sensing for reducing the amount of measurements required to perform CT. This paper tackles the problem of designing high-resolution coded apertures for compressed sensing computed tomography. In contrast to previous approaches, we aim at designing apertures to be used with low-resolution detectors in order to achieve super-resolution. The proposed method iteratively improves random coded apertures using a gradient descent algorithm subject to constraints in the coherence and homogeneity of the compressive sensing matrix induced by the coded aperture. Experiments with different test sets show consistent results for different transmittances, number of shots and super-resolution factors.

A Three-Dimensional Target Depth-Resolution Method with a Single-Vector Sensor.

Science.gov (United States)

Zhao, Anbang; Bi, Xuejie; Hui, Juan; Zeng, Caigao; Ma, Lin

2018-04-12

This paper mainly studies and verifies the target number category-resolution method in multi-target cases and the target depth-resolution method of aerial targets. Firstly, target depth resolution is performed by using the sign distribution of the reactive component of the vertical complex acoustic intensity; the target category and the number resolution in multi-target cases is realized with a combination of the bearing-time recording information; and the corresponding simulation verification is carried out. The algorithm proposed in this paper can distinguish between the single-target multi-line spectrum case and the multi-target multi-line spectrum case. This paper presents an improved azimuth-estimation method for multi-target cases, which makes the estimation results more accurate. Using the Monte Carlo simulation, the feasibility of the proposed target number and category-resolution algorithm in multi-target cases is verified. In addition, by studying the field characteristics of the aerial and surface targets, the simulation results verify that there is only amplitude difference between the aerial target field and the surface target field under the same environmental parameters, and an aerial target can be treated as a special case of a surface target; the aerial target category resolution can then be realized based on the sign distribution of the reactive component of the vertical acoustic intensity so as to realize three-dimensional target depth resolution. By processing data from a sea experiment, the feasibility of the proposed aerial target three-dimensional depth-resolution algorithm is verified.

Low-resolution simulations of vesicle suspensions in 2D

Science.gov (United States)

Kabacaoğlu, Gökberk; Quaife, Bryan; Biros, George

2018-03-01

Vesicle suspensions appear in many biological and industrial applications. These suspensions are characterized by rich and complex dynamics of vesicles due to their interaction with the bulk fluid, and their large deformations and nonlinear elastic properties. Many existing state-of-the-art numerical schemes can resolve such complex vesicle flows. However, even when using provably optimal algorithms, these simulations can be computationally expensive, especially for suspensions with a large number of vesicles. These high computational costs can limit the use of simulations for parameter exploration, optimization, or uncertainty quantification. One way to reduce the cost is to use low-resolution discretizations in space and time. However, it is well-known that simply reducing the resolution results in vesicle collisions, numerical instabilities, and often in erroneous results. In this paper, we investigate the effect of a number of algorithmic empirical fixes (which are commonly used by many groups) in an attempt to make low-resolution simulations more stable and more predictive. Based on our empirical studies for a number of flow configurations, we propose a scheme that attempts to integrate these fixes in a systematic way. This low-resolution scheme is an extension of our previous work [51,53]. Our low-resolution correction algorithms (LRCA) include anti-aliasing and membrane reparametrization for avoiding spurious oscillations in vesicles' membranes, adaptive time stepping and a repulsion force for handling vesicle collisions and, correction of vesicles' area and arc-length for maintaining physical vesicle shapes. We perform a systematic error analysis by comparing the low-resolution simulations of dilute and dense suspensions with their high-fidelity, fully resolved, counterparts. We observe that the LRCA enables both efficient and statistically accurate low-resolution simulations of vesicle suspensions, while it can be 10× to 100× faster.

Direct cone-beam cardiac reconstruction algorithm with cardiac banding artifact correction

International Nuclear Information System (INIS)

Taguchi, Katsuyuki; Chiang, Beshan S.; Hein, Ilmar A.

2006-01-01

Multislice helical computed tomography (CT) is a promising noninvasive technique for coronary artery imaging. Various factors can cause inconsistencies in cardiac CT data, which can result in degraded image quality. These inconsistencies may be the result of the patient physiology (e.g., heart rate variations), the nature of the data (e.g., cone-angle), or the reconstruction algorithm itself. An algorithm which provides the best temporal resolution for each slice, for example, often provides suboptimal image quality for the entire volume since the cardiac temporal resolution (TRc) changes from slice to slice. Such variations in TRc can generate strong banding artifacts in multi-planar reconstruction images or three-dimensional images. Discontinuous heart walls and coronary arteries may compromise the accuracy of the diagnosis. A β-blocker is often used to reduce and stabilize patients' heart rate but cannot eliminate the variation. In order to obtain robust and optimal image quality, a software solution that increases the temporal resolution and decreases the effect of heart rate is highly desirable. This paper proposes an ECG-correlated direct cone-beam reconstruction algorithm (TCOT-EGR) with cardiac banding artifact correction (CBC) and disconnected projections redundancy compensation technique (DIRECT). First the theory and analytical model of the cardiac temporal resolution is outlined. Next, the performance of the proposed algorithms is evaluated by using computer simulations as well as patient data. It will be shown that the proposed algorithms enhance the robustness of the image quality against inconsistencies by guaranteeing smooth transition of heart cycles used in reconstruction

Fuzzy Genetic Algorithm Based on Principal Operation and Inequity Degree

Science.gov (United States)

Li, Fachao; Jin, Chenxia

In this paper, starting from the structure of fuzzy information, by distinguishing principal indexes and assistant indexes, give comparison of fuzzy information on synthesizing effect and operation of fuzzy optimization on principal indexes transformation, further, propose axiom system of fuzzy inequity degree from essence of constraint, and give an instructive metric method; Then, combining genetic algorithm, give fuzzy optimization methods based on principal operation and inequity degree (denoted by BPO&ID-FGA, for short); Finally, consider its convergence using Markov chain theory and analyze its performance through an example. All these indicate, BPO&ID-FGA can not only effectively merge decision consciousness into the optimization process, but possess better global convergence, so it can be applied to many fuzzy optimization problems.

Optimizing Raytracing Algorithm Using CUDA

Directory of Open Access Journals (Sweden)

Sayed Ahmadreza Razian

2017-11-01

The results show that one can generate at least 11 frames per second in HD (720p resolution by GPU processor and GT 840M graphic card, using trace method. If better graphic card employ, this algorithm and program can be used to generate real-time animation.

An evaluation of SEBAL algorithm using high resolution aircraft data acquired during BEAREX07

Science.gov (United States)

Paul, G.; Gowda, P. H.; Prasad, V. P.; Howell, T. A.; Staggenborg, S.

2010-12-01

Surface Energy Balance Algorithm for Land (SEBAL) computes spatially distributed surface energy fluxes and evapotranspiration (ET) rates using a combination of empirical and deterministic equations executed in a strictly hierarchical sequence. Over the past decade SEBAL has been tested over various regions and has found its application in solving water resources and irrigation problems. This research combines high resolution remote sensing data and field measurements of the surface radiation and agro-meteorological variables to review various SEBAL steps for mapping ET in the Texas High Plains (THP). High resolution aircraft images (0.5-1.8 m) acquired during the Bushland Evapotranspiration and Agricultural Remote Sensing Experiment 2007 (BEAREX07) conducted at the USDA-ARS Conservation and Production Research Laboratory in Bushland, Texas, was utilized to evaluate the SEBAL. Accuracy of individual relationships and predicted ET were investigated using observed hourly ET rates from 4 large weighing lysimeters, each located at the center of 4.7 ha field. The uniqueness and the strength of this study come from the fact that it evaluates the SEBAL for irrigated and dryland conditions simultaneously with each lysimeter field planted to irrigated forage sorghum, irrigated forage corn, dryland clumped grain sorghum, and dryland row sorghum. Improved coefficients for the local conditions were developed for the computation of roughness length for momentum transport. The decision involved in selection of dry and wet pixels, which essentially determines the partitioning of the available energy between sensible (H) and latent (LE) heat fluxes has been discussed. The difference in roughness length referred to as the kB-1 parameter was modified in the current study. Performance of the SEBAL was evaluated using mean bias error (MBE) and root mean square error (RMSE). An RMSE of ±37.68 W m-2 and ±0.11 mm h-1 was observed for the net radiation and hourly actual ET, respectively

Coordination Logic for Repulsive Resolution Maneuvers

Science.gov (United States)

Narkawicz, Anthony J.; Munoz, Cesar A.; Dutle, Aaron M.

2016-01-01

This paper presents an algorithm for determining the direction an aircraft should maneuver in the event of a potential conflict with another aircraft. The algorithm is implicitly coordinated, meaning that with perfectly reliable computations and information, it will in- dependently provide directional information that is guaranteed to be coordinated without any additional information exchange or direct communication. The logic is inspired by the logic of TCAS II, the airborne system designed to reduce the risk of mid-air collisions between aircraft. TCAS II provides pilots with only vertical resolution advice, while the proposed algorithm, using a similar logic, provides implicitly coordinated vertical and horizontal directional advice.

Three-Dimensional Photoacoustic Tomography using Delay Multiply and Sum Beamforming Algorithm

OpenAIRE

Paridar, Roya; Mozaffarzadeh, Moein; Mahloojifar, Ali; Nasiriavanaki, Mohammadreza; Orooji, Mahdi

2018-01-01

Photoacoustic imaging (PAI), is a promising medical imaging technique that provides the high contrast of the optical imaging and the resolution of ultrasound (US) imaging. Among all the methods, Three-dimensional (3D) PAI provides a high resolution and accuracy. One of the most common algorithms for 3D PA image reconstruction is delay-and-sum (DAS). However, the quality of the reconstructed image obtained from this algorithm is not satisfying, having high level of sidelobes and a wide mainlob...

Comparison of turbulence mitigation algorithms

Science.gov (United States)

Kozacik, Stephen T.; Paolini, Aaron; Sherman, Ariel; Bonnett, James; Kelmelis, Eric

2017-07-01

When capturing imagery over long distances, atmospheric turbulence often degrades the data, especially when observation paths are close to the ground or in hot environments. These issues manifest as time-varying scintillation and warping effects that decrease the effective resolution of the sensor and reduce actionable intelligence. In recent years, several image processing approaches to turbulence mitigation have shown promise. Each of these algorithms has different computational requirements, usability demands, and degrees of independence from camera sensors. They also produce different degrees of enhancement when applied to turbulent imagery. Additionally, some of these algorithms are applicable to real-time operational scenarios while others may only be suitable for postprocessing workflows. EM Photonics has been developing image-processing-based turbulence mitigation technology since 2005. We will compare techniques from the literature with our commercially available, real-time, GPU-accelerated turbulence mitigation software. These comparisons will be made using real (not synthetic), experimentally obtained data for a variety of conditions, including varying optical hardware, imaging range, subjects, and turbulence conditions. Comparison metrics will include image quality, video latency, computational complexity, and potential for real-time operation. Additionally, we will present a technique for quantitatively comparing turbulence mitigation algorithms using real images of radial resolution targets.

Topic shift impairs pronoun resolution during sentence comprehension: Evidence from event-related potentials.

Science.gov (United States)

Xu, Xiaodong; Zhou, Xiaolin

2016-02-01

This study investigated how topic shift and topic continuation influence pronoun interpretation in Chinese. ERPs recorded on pronouns in topic structure showed stronger and earlier late positive responses (P600) for the topic-shift than for the topic-continuation conditions. However, in nontopic structure where the subject (denoting only subjecthood), rather than the topic (denoting both topichood and subjecthood), acted as the antecedent of the pronoun, almost indistinguishable P600 responses were obtained on the pronoun regardless of whether it was referring to the subject (i.e., subject continuation) or the object (i.e., subject shift). Moreover, stronger and earlier P600 responses were elicited by pronouns in the topic-shift than in the subject-shift conditions, although there was no difference between the topic-continuation and the subject-continuation conditions. These findings suggest that topic shift results in greater difficulty in the resolution stage of referential processing, although the bonding process is not sensitive to the manipulation of topic status, and that topic has a privileged cognitive status relative to other nontopic entities (e.g., subject) in real-time language processing. © 2015 Society for Psychophysiological Research.

Droplet Image Super Resolution Based on Sparse Representation and Kernel Regression

Science.gov (United States)

Zou, Zhenzhen; Luo, Xinghong; Yu, Qiang

2018-05-01

Microgravity and containerless conditions, which are produced via electrostatic levitation combined with a drop tube, are important when studying the intrinsic properties of new metastable materials. Generally, temperature and image sensors can be used to measure the changes of sample temperature, morphology and volume. Then, the specific heat, surface tension, viscosity changes and sample density can be obtained. Considering that the falling speed of the material sample droplet is approximately 31.3 m/s when it reaches the bottom of a 50-meter-high drop tube, a high-speed camera with a collection rate of up to 106 frames/s is required to image the falling droplet. However, at the high-speed mode, very few pixels, approximately 48-120, will be obtained in each exposure time, which results in low image quality. Super-resolution image reconstruction is an algorithm that provides finer details than the sampling grid of a given imaging device by increasing the number of pixels per unit area in the image. In this work, we demonstrate the application of single image-resolution reconstruction in the microgravity and electrostatic levitation for the first time. Here, using the image super-resolution method based on sparse representation, a low-resolution droplet image can be reconstructed. Employed Yang's related dictionary model, high- and low-resolution image patches were combined with dictionary training, and high- and low-resolution-related dictionaries were obtained. The online double-sparse dictionary training algorithm was used in the study of related dictionaries and overcome the shortcomings of the traditional training algorithm with small image patch. During the stage of image reconstruction, the algorithm of kernel regression is added, which effectively overcomes the shortcomings of the Yang image's edge blurs.

Double-resolution electron holography with simple Fourier transform of fringe-shifted holograms

International Nuclear Information System (INIS)

Volkov, V.V.; Han, M.G.; Zhu, Y.

2013-01-01

We propose a fringe-shifting holographic method with an appropriate image wave recovery algorithm leading to exact solution of holographic equations. With this new method the complex object image wave recovered from holograms appears to have much less traditional artifacts caused by the autocorrelation band present practically in all Fourier transformed holograms. The new analytical solutions make possible a double-resolution electron holography free from autocorrelation band artifacts and thus push the limits for phase resolution. The new image wave recovery algorithm uses a popular Fourier solution of the side band-pass filter technique, while the fringe-shifting holographic method is simple to implement in practice. - Highlights: • We propose a fringe-shifting holographic method simple enough for practical implementations. • Our new image-wave-recovery algorithm follows from exact solution of holographic equations. • With autocorrelation band removal from holograms it is possible to achieve double-resolution electron holography data free from several commonly known artifacts. • The new fringe-shifting method can reach an image wave resolution close to single fringe spacing

Double-resolution electron holography with simple Fourier transform of fringe-shifted holograms

Energy Technology Data Exchange (ETDEWEB)

Volkov, V.V., E-mail: volkov@bnl.gov; Han, M.G.; Zhu, Y.

2013-11-15

We propose a fringe-shifting holographic method with an appropriate image wave recovery algorithm leading to exact solution of holographic equations. With this new method the complex object image wave recovered from holograms appears to have much less traditional artifacts caused by the autocorrelation band present practically in all Fourier transformed holograms. The new analytical solutions make possible a double-resolution electron holography free from autocorrelation band artifacts and thus push the limits for phase resolution. The new image wave recovery algorithm uses a popular Fourier solution of the side band-pass filter technique, while the fringe-shifting holographic method is simple to implement in practice. - Highlights: • We propose a fringe-shifting holographic method simple enough for practical implementations. • Our new image-wave-recovery algorithm follows from exact solution of holographic equations. • With autocorrelation band removal from holograms it is possible to achieve double-resolution electron holography data free from several commonly known artifacts. • The new fringe-shifting method can reach an image wave resolution close to single fringe spacing.

Time Optimized Algorithm for Web Document Presentation Adaptation

DEFF Research Database (Denmark)

Pan, Rong; Dolog, Peter

2010-01-01

Currently information on the web is accessed through different devices. Each device has its own properties such as resolution, size, and capabilities to display information in different format and so on. This calls for adaptation of information presentation for such platforms. This paper proposes...... content-optimized and time-optimized algorithms for information presentation adaptation for different devices based on its hierarchical model. The model is formalized in order to experiment with different algorithms.......Currently information on the web is accessed through different devices. Each device has its own properties such as resolution, size, and capabilities to display information in different format and so on. This calls for adaptation of information presentation for such platforms. This paper proposes...

Windowed time-reversal music technique for super-resolution ultrasound imaging

Science.gov (United States)

Huang, Lianjie; Labyed, Yassin

2018-05-01

Systems and methods for super-resolution ultrasound imaging using a windowed and generalized TR-MUSIC algorithm that divides the imaging region into overlapping sub-regions and applies the TR-MUSIC algorithm to the windowed backscattered ultrasound signals corresponding to each sub-region. The algorithm is also structured to account for the ultrasound attenuation in the medium and the finite-size effects of ultrasound transducer elements.

Projections onto Convex Sets Super-Resolution Reconstruction Based on Point Spread Function Estimation of Low-Resolution Remote Sensing Images

Directory of Open Access Journals (Sweden)

Chong Fan

2017-02-01

Full Text Available To solve the problem on inaccuracy when estimating the point spread function (PSF of the ideal original image in traditional projection onto convex set (POCS super-resolution (SR reconstruction, this paper presents an improved POCS SR algorithm based on PSF estimation of low-resolution (LR remote sensing images. The proposed algorithm can improve the spatial resolution of the image and benefit agricultural crop visual interpolation. The PSF of the highresolution (HR image is unknown in reality. Therefore, analysis of the relationship between the PSF of the HR image and the PSF of the LR image is important to estimate the PSF of the HR image by using multiple LR images. In this study, the linear relationship between the PSFs of the HR and LR images can be proven. In addition, the novel slant knife-edge method is employed, which can improve the accuracy of the PSF estimation of LR images. Finally, the proposed method is applied to reconstruct airborne digital sensor 40 (ADS40 three-line array images and the overlapped areas of two adjacent GF-2 images by embedding the estimated PSF of the HR image to the original POCS SR algorithm. Experimental results show that the proposed method yields higher quality of reconstructed images than that produced by the blind SR method and the bicubic interpolation method.

A Modified Spatiotemporal Fusion Algorithm Using Phenological Information for Predicting Reflectance of Paddy Rice in Southern China

Directory of Open Access Journals (Sweden)

Mengxue Liu

2018-05-01

Full Text Available Satellite data for studying surface dynamics in heterogeneous landscapes are missing due to frequent cloud contamination, low temporal resolution, and technological difficulties in developing satellites. A modified spatiotemporal fusion algorithm for predicting the reflectance of paddy rice is presented in this paper. The algorithm uses phenological information extracted from a moderate-resolution imaging spectroradiometer enhanced vegetation index time series to improve the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM. The algorithm is tested with satellite data on Yueyang City, China. The main contribution of the modified algorithm is the selection of similar neighborhood pixels by using phenological information to improve accuracy. Results show that the modified algorithm performs better than ESTARFM in visual inspection and quantitative metrics, especially for paddy rice. This modified algorithm provides not only new ideas for the improvement of spatiotemporal data fusion method, but also technical support for the generation of remote sensing data with high spatial and temporal resolution.

Texton-based super-resolution for achieving high spatiotemporal resolution in hybrid camera system

Science.gov (United States)

Kamimura, Kenji; Tsumura, Norimichi; Nakaguchi, Toshiya; Miyake, Yoichi

2010-05-01

Many super-resolution methods have been proposed to enhance the spatial resolution of images by using iteration and multiple input images. In a previous paper, we proposed the example-based super-resolution method to enhance an image through pixel-based texton substitution to reduce the computational cost. In this method, however, we only considered the enhancement of a texture image. In this study, we modified this texton substitution method for a hybrid camera to reduce the required bandwidth of a high-resolution video camera. We applied our algorithm to pairs of high- and low-spatiotemporal-resolution videos, which were synthesized to simulate a hybrid camera. The result showed that the fine detail of the low-resolution video can be reproduced compared with bicubic interpolation and the required bandwidth could be reduced to about 1/5 in a video camera. It was also shown that the peak signal-to-noise ratios (PSNRs) of the images improved by about 6 dB in a trained frame and by 1.0-1.5 dB in a test frame, as determined by comparison with the processed image using bicubic interpolation, and the average PSNRs were higher than those obtained by the well-known Freeman’s patch-based super-resolution method. Compared with that of the Freeman’s patch-based super-resolution method, the computational time of our method was reduced to almost 1/10.

Extended reactance domain algorithms for DoA estimation onto an ESPAR antennas

Science.gov (United States)

Harabi, F.; Akkar, S.; Gharsallah, A.

2016-07-01

Based on an extended reactance domain (RD) covariance matrix, this article proposes new alternatives for directions of arrival (DoAs) estimation of narrowband sources through an electronically steerable parasitic array radiator (ESPAR) antennas. Because of the centro symmetry of the classic ESPAR antennas, an unitary transformation is applied to the collected data that allow an important reduction in both computational cost and processing time and, also, an enhancement of the resolution capabilities of the proposed algorithms. Moreover, this article proposes a new approach for eigenvalues estimation through only some linear operations. The developed DoAs estimation algorithms based on this new approach has illustrated a good behaviour with less calculation cost and processing time as compared to other schemes based on the classic eigenvalues approach. The conducted simulations demonstrate that high-precision and high-resolution DoAs estimation can be reached especially in very closely sources situation and low sources power as compared to the RD-MUSIC algorithm and the RD-PM algorithm. The asymptotic behaviours of the proposed DoAs estimators are analysed in various scenarios and compared with the Cramer-Rao bound (CRB). The conducted simulations testify the high-resolution of the developed algorithms and prove the efficiently of the proposed approach.

Super-resolution for imagery from integrated microgrid polarimeters.

Science.gov (United States)

Hardie, Russell C; LeMaster, Daniel A; Ratliff, Bradley M

2011-07-04

Imagery from microgrid polarimeters is obtained by using a mosaic of pixel-wise micropolarizers on a focal plane array (FPA). Each distinct polarization image is obtained by subsampling the full FPA image. Thus, the effective pixel pitch for each polarization channel is increased and the sampling frequency is decreased. As a result, aliasing artifacts from such undersampling can corrupt the true polarization content of the scene. Here we present the first multi-channel multi-frame super-resolution (SR) algorithms designed specifically for the problem of image restoration in microgrid polarization imagers. These SR algorithms can be used to address aliasing and other degradations, without sacrificing field of view or compromising optical resolution with an anti-aliasing filter. The new SR methods are designed to exploit correlation between the polarimetric channels. One of the new SR algorithms uses a form of regularized least squares and has an iterative solution. The other is based on the faster adaptive Wiener filter SR method. We demonstrate that the new multi-channel SR algorithms are capable of providing significant enhancement of polarimetric imagery and that they outperform their independent channel counterparts.

Research on compressive sensing reconstruction algorithm based on total variation model

Science.gov (United States)

Gao, Yu-xuan; Sun, Huayan; Zhang, Tinghua; Du, Lin

2017-12-01

Compressed sensing for breakthrough Nyquist sampling theorem provides a strong theoretical , making compressive sampling for image signals be carried out simultaneously. In traditional imaging procedures using compressed sensing theory, not only can it reduces the storage space, but also can reduce the demand for detector resolution greatly. Using the sparsity of image signal, by solving the mathematical model of inverse reconfiguration, realize the super-resolution imaging. Reconstruction algorithm is the most critical part of compression perception, to a large extent determine the accuracy of the reconstruction of the image.The reconstruction algorithm based on the total variation (TV) model is more suitable for the compression reconstruction of the two-dimensional image, and the better edge information can be obtained. In order to verify the performance of the algorithm, Simulation Analysis the reconstruction result in different coding mode of the reconstruction algorithm based on the TV reconstruction algorithm. The reconstruction effect of the reconfigurable algorithm based on TV based on the different coding methods is analyzed to verify the stability of the algorithm. This paper compares and analyzes the typical reconstruction algorithm in the same coding mode. On the basis of the minimum total variation algorithm, the Augmented Lagrangian function term is added and the optimal value is solved by the alternating direction method.Experimental results show that the reconstruction algorithm is compared with the traditional classical algorithm based on TV has great advantages, under the low measurement rate can be quickly and accurately recovers target image.

Image-reconstruction algorithms for positron-emission tomography systems

International Nuclear Information System (INIS)

Cheng, S.N.C.

1982-01-01

The positional uncertainty in the time-of-flight measurement of a positron-emission tomography system is modelled as a Gaussian distributed random variable and the image is assumed to be piecewise constant on a rectilinear lattice. A reconstruction algorithm using maximum-likelihood estimation is derived for the situation in which time-of-flight data are sorted as the most-likely-position array. The algorithm is formulated as a linear system described by a nonseparable, block-banded, Toeplitz matrix, and a sine-transform technique is used to implement this algorithm efficiently. The reconstruction algorithms for both the most-likely-position array and the confidence-weighted array are described by similar equations, hence similar linear systems can be used to described the reconstruction algorithm for a discrete, confidence-weighted array, when the matrix and the entries in the data array are properly identified. It is found that the mean square-error depends on the ratio of the full width at half the maximum of time-of-flight measurement over the size of a pixel. When other parameters are fixed, the larger the pixel size, the smaller is the mean square-error. In the study of resolution, parameters that affect the impulse response of time-of-flight reconstruction algorithms are identified. It is found that the larger the pixel size, the larger is the standard deviation of the impulse response. This shows that small mean square-error and fine resolution are two contradictory requirements

Bayesian Peptide Peak Detection for High Resolution TOF Mass Spectrometry.

Science.gov (United States)

Zhang, Jianqiu; Zhou, Xiaobo; Wang, Honghui; Suffredini, Anthony; Zhang, Lin; Huang, Yufei; Wong, Stephen

2010-11-01

In this paper, we address the issue of peptide ion peak detection for high resolution time-of-flight (TOF) mass spectrometry (MS) data. A novel Bayesian peptide ion peak detection method is proposed for TOF data with resolution of 10 000-15 000 full width at half-maximum (FWHW). MS spectra exhibit distinct characteristics at this resolution, which are captured in a novel parametric model. Based on the proposed parametric model, a Bayesian peak detection algorithm based on Markov chain Monte Carlo (MCMC) sampling is developed. The proposed algorithm is tested on both simulated and real datasets. The results show a significant improvement in detection performance over a commonly employed method. The results also agree with expert's visual inspection. Moreover, better detection consistency is achieved across MS datasets from patients with identical pathological condition.

Double-Stage Delay Multiply and Sum Beamforming Algorithm: Application to Linear-Array Photoacoustic Imaging.

Science.gov (United States)

Mozaffarzadeh, Moein; Mahloojifar, Ali; Orooji, Mahdi; Adabi, Saba; Nasiriavanaki, Mohammadreza

2018-01-01

Photoacoustic imaging (PAI) is an emerging medical imaging modality capable of providing high spatial resolution of Ultrasound (US) imaging and high contrast of optical imaging. Delay-and-Sum (DAS) is the most common beamforming algorithm in PAI. However, using DAS beamformer leads to low resolution images and considerable contribution of off-axis signals. A new paradigm namely delay-multiply-and-sum (DMAS), which was originally used as a reconstruction algorithm in confocal microwave imaging, was introduced to overcome the challenges in DAS. DMAS was used in PAI systems and it was shown that this algorithm results in resolution improvement and sidelobe degrading. However, DMAS is still sensitive to high levels of noise, and resolution improvement is not satisfying. Here, we propose a novel algorithm based on DAS algebra inside DMAS formula expansion, double stage DMAS (DS-DMAS), which improves the image resolution and levels of sidelobe, and is much less sensitive to high level of noise compared to DMAS. The performance of DS-DMAS algorithm is evaluated numerically and experimentally. The resulted images are evaluated qualitatively and quantitatively using established quality metrics including signal-to-noise ratio (SNR), full-width-half-maximum (FWHM) and contrast ratio (CR). It is shown that DS-DMAS outperforms DAS and DMAS at the expense of higher computational load. DS-DMAS reduces the lateral valley for about 15 dB and improves the SNR and FWHM better than 13% and 30%, respectively. Moreover, the levels of sidelobe are reduced for about 10 dB in comparison with those in DMAS.

Evaluation of a New Backtrack Free Path Planning Algorithm for Manipulators

Science.gov (United States)

Islam, Md. Nazrul; Tamura, Shinsuke; Murata, Tomonari; Yanase, Tatsuro

This paper evaluates a newly proposed backtrack free path planning algorithm (BFA) for manipulators. BFA is an exact algorithm, i.e. it is resolution complete. Different from existing resolution complete algorithms, its computation time and memory space are proportional to the number of arms. Therefore paths can be calculated within practical and predetermined time even for manipulators with many arms, and it becomes possible to plan complicated motions of multi-arm manipulators in fully automated environments. The performance of BFA is evaluated for 2-dimensional environments while changing the number of arms and obstacle placements. Its performance under locus and attitude constraints is also evaluated. Evaluation results show that the computation volume of the algorithm is almost the same as the theoretical one, i.e. it increases linearly with the number of arms even in complicated environments. Moreover BFA achieves the constant performance independent of environments.

Open-source algorithm for detecting sea ice surface features in high-resolution optical imagery

Directory of Open Access Journals (Sweden)

N. C. Wright

2018-04-01

Full Text Available Snow, ice, and melt ponds cover the surface of the Arctic Ocean in fractions that change throughout the seasons. These surfaces control albedo and exert tremendous influence over the energy balance in the Arctic. Increasingly available meter- to decimeter-scale resolution optical imagery captures the evolution of the ice and ocean surface state visually, but methods for quantifying coverage of key surface types from raw imagery are not yet well established. Here we present an open-source system designed to provide a standardized, automated, and reproducible technique for processing optical imagery of sea ice. The method classifies surface coverage into three main categories: snow and bare ice, melt ponds and submerged ice, and open water. The method is demonstrated on imagery from four sensor platforms and on imagery spanning from spring thaw to fall freeze-up. Tests show the classification accuracy of this method typically exceeds 96 %. To facilitate scientific use, we evaluate the minimum observation area required for reporting a representative sample of surface coverage. We provide an open-source distribution of this algorithm and associated training datasets and suggest the community consider this a step towards standardizing optical sea ice imagery processing. We hope to encourage future collaborative efforts to improve the code base and to analyze large datasets of optical sea ice imagery.

Open-source algorithm for detecting sea ice surface features in high-resolution optical imagery

Science.gov (United States)

Wright, Nicholas C.; Polashenski, Chris M.

2018-04-01

Snow, ice, and melt ponds cover the surface of the Arctic Ocean in fractions that change throughout the seasons. These surfaces control albedo and exert tremendous influence over the energy balance in the Arctic. Increasingly available meter- to decimeter-scale resolution optical imagery captures the evolution of the ice and ocean surface state visually, but methods for quantifying coverage of key surface types from raw imagery are not yet well established. Here we present an open-source system designed to provide a standardized, automated, and reproducible technique for processing optical imagery of sea ice. The method classifies surface coverage into three main categories: snow and bare ice, melt ponds and submerged ice, and open water. The method is demonstrated on imagery from four sensor platforms and on imagery spanning from spring thaw to fall freeze-up. Tests show the classification accuracy of this method typically exceeds 96 %. To facilitate scientific use, we evaluate the minimum observation area required for reporting a representative sample of surface coverage. We provide an open-source distribution of this algorithm and associated training datasets and suggest the community consider this a step towards standardizing optical sea ice imagery processing. We hope to encourage future collaborative efforts to improve the code base and to analyze large datasets of optical sea ice imagery.

Comparison between iterative wavefront control algorithm and direct gradient wavefront control algorithm for adaptive optics system

International Nuclear Information System (INIS)

Cheng Sheng-Yi; Liu Wen-Jin; Chen Shan-Qiu; Dong Li-Zhi; Yang Ping; Xu Bing

2015-01-01

Among all kinds of wavefront control algorithms in adaptive optics systems, the direct gradient wavefront control algorithm is the most widespread and common method. This control algorithm obtains the actuator voltages directly from wavefront slopes through pre-measuring the relational matrix between deformable mirror actuators and Hartmann wavefront sensor with perfect real-time characteristic and stability. However, with increasing the number of sub-apertures in wavefront sensor and deformable mirror actuators of adaptive optics systems, the matrix operation in direct gradient algorithm takes too much time, which becomes a major factor influencing control effect of adaptive optics systems. In this paper we apply an iterative wavefront control algorithm to high-resolution adaptive optics systems, in which the voltages of each actuator are obtained through iteration arithmetic, which gains great advantage in calculation and storage. For AO system with thousands of actuators, the computational complexity estimate is about O(n 2 ) ∼ O(n 3 ) in direct gradient wavefront control algorithm, while the computational complexity estimate in iterative wavefront control algorithm is about O(n) ∼ (O(n) 3/2 ), in which n is the number of actuators of AO system. And the more the numbers of sub-apertures and deformable mirror actuators, the more significant advantage the iterative wavefront control algorithm exhibits. (paper)

Surface electromyography based muscle fatigue detection using high-resolution time-frequency methods and machine learning algorithms.

Science.gov (United States)

Karthick, P A; Ghosh, Diptasree Maitra; Ramakrishnan, S

2018-02-01

Surface electromyography (sEMG) based muscle fatigue research is widely preferred in sports science and occupational/rehabilitation studies due to its noninvasiveness. However, these signals are complex, multicomponent and highly nonstationary with large inter-subject variations, particularly during dynamic contractions. Hence, time-frequency based machine learning methodologies can improve the design of automated system for these signals. In this work, the analysis based on high-resolution time-frequency methods, namely, Stockwell transform (S-transform), B-distribution (BD) and extended modified B-distribution (EMBD) are proposed to differentiate the dynamic muscle nonfatigue and fatigue conditions. The nonfatigue and fatigue segments of sEMG signals recorded from the biceps brachii of 52 healthy volunteers are preprocessed and subjected to S-transform, BD and EMBD. Twelve features are extracted from each method and prominent features are selected using genetic algorithm (GA) and binary particle swarm optimization (BPSO). Five machine learning algorithms, namely, naïve Bayes, support vector machine (SVM) of polynomial and radial basis kernel, random forest and rotation forests are used for the classification. The results show that all the proposed time-frequency distributions (TFDs) are able to show the nonstationary variations of sEMG signals. Most of the features exhibit statistically significant difference in the muscle fatigue and nonfatigue conditions. The maximum number of features (66%) is reduced by GA and BPSO for EMBD and BD-TFD respectively. The combination of EMBD- polynomial kernel based SVM is found to be most accurate (91% accuracy) in classifying the conditions with the features selected using GA. The proposed methods are found to be capable of handling the nonstationary and multicomponent variations of sEMG signals recorded in dynamic fatiguing contractions. Particularly, the combination of EMBD- polynomial kernel based SVM could be used to

Accurate 3D reconstruction by a new PDS-OSEM algorithm for HRRT

Science.gov (United States)

Chen, Tai-Been; Horng-Shing Lu, Henry; Kim, Hang-Keun; Son, Young-Don; Cho, Zang-Hee

2014-03-01

State-of-the-art high resolution research tomography (HRRT) provides high resolution PET images with full 3D human brain scanning. But, a short time frame in dynamic study causes many problems related to the low counts in the acquired data. The PDS-OSEM algorithm was proposed to reconstruct the HRRT image with a high signal-to-noise ratio that provides accurate information for dynamic data. The new algorithm was evaluated by simulated image, empirical phantoms, and real human brain data. Meanwhile, the time activity curve was adopted to validate a reconstructed performance of dynamic data between PDS-OSEM and OP-OSEM algorithms. According to simulated and empirical studies, the PDS-OSEM algorithm reconstructs images with higher quality, higher accuracy, less noise, and less average sum of square error than those of OP-OSEM. The presented algorithm is useful to provide quality images under the condition of low count rates in dynamic studies with a short scan time.

MULTI-SCALE SEGMENTATION OF HIGH RESOLUTION REMOTE SENSING IMAGES BY INTEGRATING MULTIPLE FEATURES

Directory of Open Access Journals (Sweden)

Y. Di

2017-05-01

Full Text Available Most of multi-scale segmentation algorithms are not aiming at high resolution remote sensing images and have difficulty to communicate and use layers’ information. In view of them, we proposes a method of multi-scale segmentation of high resolution remote sensing images by integrating multiple features. First, Canny operator is used to extract edge information, and then band weighted distance function is built to obtain the edge weight. According to the criterion, the initial segmentation objects of color images can be gained by Kruskal minimum spanning tree algorithm. Finally segmentation images are got by the adaptive rule of Mumford–Shah region merging combination with spectral and texture information. The proposed method is evaluated precisely using analog images and ZY-3 satellite images through quantitative and qualitative analysis. The experimental results show that the multi-scale segmentation of high resolution remote sensing images by integrating multiple features outperformed the software eCognition fractal network evolution algorithm (highest-resolution network evolution that FNEA on the accuracy and slightly inferior to FNEA on the efficiency.

Improved Synthesis of Global Irradiance with One-Minute Resolution for PV System Simulations

Directory of Open Access Journals (Sweden)

Martin Hofmann

2014-01-01

Full Text Available High resolution global irradiance time series are needed for accurate simulations of photovoltaic (PV systems, since the typical volatile PV power output induced by fast irradiance changes cannot be simulated properly with commonly available hourly averages of global irradiance. We present a two-step algorithm that is capable of synthesizing one-minute global irradiance time series based on hourly averaged datasets. The algorithm is initialized by deriving characteristic transition probability matrices (TPM for different weather conditions (cloudless, broken clouds and overcast from a large number of high resolution measurements. Once initialized, the algorithm is location-independent and capable of synthesizing one-minute values based on hourly averaged global irradiance of any desired location. The one-minute time series are derived by discrete-time Markov chains based on a TPM that matches the weather condition of the input dataset. One-minute time series generated with the presented algorithm are compared with measured high resolution data and show a better agreement compared to two existing synthesizing algorithms in terms of temporal variability and characteristic frequency distributions of global irradiance and clearness index values. A comparison based on measurements performed in Lindenberg, Germany, and Carpentras, France, shows a reduction of the frequency distribution root mean square errors of more than 60% compared to the two existing synthesizing algorithms.

Super-resolution reconstruction of 4D-CT lung data via patch-based low-rank matrix reconstruction

Science.gov (United States)

Fang, Shiting; Wang, Huafeng; Liu, Yueliang; Zhang, Minghui; Yang, Wei; Feng, Qianjin; Chen, Wufan; Zhang, Yu

2017-10-01

Lung 4D computed tomography (4D-CT), which is a time-resolved CT data acquisition, performs an important role in explicitly including respiratory motion in treatment planning and delivery. However, the radiation dose is usually reduced at the expense of inter-slice spatial resolution to minimize radiation-related health risk. Therefore, resolution enhancement along the superior-inferior direction is necessary. In this paper, a super-resolution (SR) reconstruction method based on a patch low-rank matrix reconstruction is proposed to improve the resolution of lung 4D-CT images. Specifically, a low-rank matrix related to every patch is constructed by using a patch searching strategy. Thereafter, the singular value shrinkage is employed to recover the high-resolution patch under the constraints of the image degradation model. The output high-resolution patches are finally assembled to output the entire image. This method is extensively evaluated using two public data sets. Quantitative analysis shows that the proposed algorithm decreases the root mean square error by 9.7%-33.4% and the edge width by 11.4%-24.3%, relative to linear interpolation, back projection (BP) and Zhang et al’s algorithm. A new algorithm has been developed to improve the resolution of 4D-CT. In all experiments, the proposed method outperforms various interpolation methods, as well as BP and Zhang et al’s method, thus indicating the effectivity and competitiveness of the proposed algorithm.

EUV lithography for 22nm half pitch and beyond: exploring resolution, LWR, and sensitivity tradeoffs

Science.gov (United States)

Putna, E. Steve; Younkin, Todd R.; Leeson, Michael; Caudillo, Roman; Bacuita, Terence; Shah, Uday; Chandhok, Manish

2011-04-01

The International Technology Roadmap for Semiconductors (ITRS) denotes Extreme Ultraviolet (EUV) lithography as a leading technology option for realizing the 22nm half pitch node and beyond. According to recent assessments made at the 2010 EUVL Symposium, the readiness of EUV materials remains one of the top risk items for EUV adoption. The main development issue regarding EUV resists has been how to simultaneously achieve high resolution, high sensitivity, and low line width roughness (LWR). This paper describes our strategy, the current status of EUV materials, and the integrated post-development LWR reduction efforts made at Intel Corporation. Data collected utilizing Intel's Micro- Exposure Tool (MET) is presented in order to examine the feasibility of establishing a resist process that simultaneously exhibits <=22nm half-pitch (HP) L/S resolution at <=11.3mJ/cm2 with <=3nm LWR.

Two-dimensional Fast ESPRIT Algorithm for Linear Array SAR Imaging

Directory of Open Access Journals (Sweden)

Zhao Yi-chao

2015-10-01

Full Text Available The linear array Synthetic Aperture Radar (SAR system is a popular research tool, because it can realize three-dimensional imaging. However, owning to limitations of the aircraft platform and actual conditions, resolution improvement is difficult in cross-track and along-track directions. In this study, a twodimensional fast Estimation of Signal Parameters by Rotational Invariance Technique (ESPRIT algorithm for linear array SAR imaging is proposed to overcome these limitations. This approach combines the Gerschgorin disks method and the ESPRIT algorithm to estimate the positions of scatterers in cross and along-rack directions. Moreover, the reflectivity of scatterers is obtained by a modified pairing method based on “region growing”, replacing the least-squares method. The simulation results demonstrate the applicability of the algorithm with high resolution, quick calculation, and good real-time response.

An efficient and fast detection algorithm for multimode FBG sensing

DEFF Research Database (Denmark)

Ganziy, Denis; Jespersen, O.; Rose, B.

2015-01-01

We propose a novel dynamic gate algorithm (DGA) for fast and accurate peak detection. The algorithm uses threshold determined detection window and Center of gravity algorithm with bias compensation. We analyze the wavelength fit resolution of the DGA for different values of signal to noise ratio...... and different typical peak shapes. Our simulations and experiments demonstrate that the DGA method is fast and robust with higher stability and accuracy compared to conventional algorithms. This makes it very attractive for future implementation in sensing systems especially based on multimode fiber Bragg...

Design of 4D x-ray tomography experiments for reconstruction using regularized iterative algorithms

Science.gov (United States)

Mohan, K. Aditya

2017-10-01

4D X-ray computed tomography (4D-XCT) is widely used to perform non-destructive characterization of time varying physical processes in various materials. The conventional approach to improving temporal resolution in 4D-XCT involves the development of expensive and complex instrumentation that acquire data faster with reduced noise. It is customary to acquire data with many tomographic views at a high signal to noise ratio. Instead, temporal resolution can be improved using regularized iterative algorithms that are less sensitive to noise and limited views. These algorithms benefit from optimization of other parameters such as the view sampling strategy while improving temporal resolution by reducing the total number of views or the detector exposure time. This paper presents the design principles of 4D-XCT experiments when using regularized iterative algorithms derived using the framework of model-based reconstruction. A strategy for performing 4D-XCT experiments is presented that allows for improving the temporal resolution by progressively reducing the number of views or the detector exposure time. Theoretical analysis of the effect of the data acquisition parameters on the detector signal to noise ratio, spatial reconstruction resolution, and temporal reconstruction resolution is also presented in this paper.

Catheter Calibration Using Template Matching Line Interpolation Algorithm

National Research Council Canada - National Science Library

Nagy, L

2001-01-01

..., such as: image resolution, type of the calibration, algorithm used for contour detection, size of the FOV, other parameters of the image The studied calibration method is the one using catheter size...

Identification of overlapping communities and their hierarchy by locally calculating community-changing resolution levels

OpenAIRE

Havemann, Frank; Heinz, Michael; Struck, Alexander; Gläser, Jochen

2010-01-01

We propose a new local, deterministic and parameter-free algorithm that detects fuzzy and crisp overlapping communities in a weighted network and simultaneously reveals their hierarchy. Using a local fitness function, the algorithm greedily expands natural communities of seeds until the whole graph is covered. The hierarchy of communities is obtained analytically by calculating resolution levels at which communities grow rather than numerically by testing different resolution levels. This ana...

A hybrid genetic algorithm and linear regression for prediction of NOx emission in power generation plant

International Nuclear Information System (INIS)

Bunyamin, Muhammad Afif; Yap, Keem Siah; Aziz, Nur Liyana Afiqah Abdul; Tiong, Sheih Kiong; Wong, Shen Yuong; Kamal, Md Fauzan

2013-01-01

This paper presents a new approach of gas emission estimation in power generation plant using a hybrid Genetic Algorithm (GA) and Linear Regression (LR) (denoted as GA-LR). The LR is one of the approaches that model the relationship between an output dependant variable, y, with one or more explanatory variables or inputs which denoted as x. It is able to estimate unknown model parameters from inputs data. On the other hand, GA is used to search for the optimal solution until specific criteria is met causing termination. These results include providing good solutions as compared to one optimal solution for complex problems. Thus, GA is widely used as feature selection. By combining the LR and GA (GA-LR), this new technique is able to select the most important input features as well as giving more accurate prediction by minimizing the prediction errors. This new technique is able to produce more consistent of gas emission estimation, which may help in reducing population to the environment. In this paper, the study's interest is focused on nitrous oxides (NOx) prediction. The results of the experiment are encouraging.

Evaluation of reconstruction algorithms in SPECT neuroimaging: Pt. 1

International Nuclear Information System (INIS)

Heejoung Kim; Zeeberg, B.R.; Reba, R.C.

1993-01-01

In the presence of statistical noise, an iterative reconstruction algorithm (IRA) for the quantitative reconstruction of single-photon-emission computed tomographic (SPECT) brain images overcomes major limitations of applying the standard filtered back projection (FBP) reconstruction algorithm to projection data which have been degraded by convolution of the true radioactivity distribution with a finite-resolution distance-dependent detector response: (a) the non-uniformity within the grey (or white) matter voxels which results even though the true model is uniform within these voxels; (b) a significantly lower ratio of grey/white matter voxel values than in the true model; and (c) an inability to detect an altered radioactivity value within the grey (or white) matter voxels. It is normally expected that an algorithm which improves spatial resolution and quantitative accuracy might also increase the magnitude of the statistical noise in the reconstructed image. However, the noise properties in the IRA images are very similar to those in the FBP images. (Author)

A fast autofocus algorithm for synthetic aperture radar processing

DEFF Research Database (Denmark)

Dall, Jørgen

1992-01-01

High-resolution synthetic aperture radar (SAR) imaging requires the motion of the radar platform to be known very accurately. Otherwise, phase errors are induced in the processing of the raw SAR data, and bad focusing results. In particular, a constant error in the measured along-track velocity o...... of magnitude lower than that of other algorithms providing comparable accuracies is presented. The algorithm has been tested on data from the Danish Airborne SAR, and the performance is compared with that of the traditional map drift algorithm...

A medium resolution fingerprint matching system

Directory of Open Access Journals (Sweden)

Ayman Mohammad Bahaa-Eldin

2013-09-01

Full Text Available In this paper, a novel minutiae based fingerprint matching system is proposed. The system is suitable for medium resolution fingerprint images obtained by low cost commercial sensors. The paper presents a new thinning algorithm, a new features extraction and representation, and a novel feature distance matching algorithm. The proposed system is rotation and translation invariant and is suitable for complete or partial fingerprint matching. The proposed algorithms are optimized to be executed on low resource environments both in CPU power and memory space. The system was evaluated using a standard fingerprint dataset and good performance and accuracy were achieved under certain image quality requirements. In addition, the proposed system was compared favorably to that of the state of the art systems.

High-Resolution PET Detector. Final report

International Nuclear Information System (INIS)

Karp, Joel

2014-01-01

The objective of this project was to develop an understanding of the limits of performance for a high resolution PET detector using an approach based on continuous scintillation crystals rather than pixelated crystals. The overall goal was to design a high-resolution detector, which requires both high spatial resolution and high sensitivity for 511 keV gammas. Continuous scintillation detectors (Anger cameras) have been used extensively for both single-photon and PET scanners, however, these instruments were based on NaI(Tl) scintillators using relatively large, individual photo-multipliers. In this project we investigated the potential of this type of detector technology to achieve higher spatial resolution through the use of improved scintillator materials and photo-sensors, and modification of the detector surface to optimize the light response function.We achieved an average spatial resolution of 3-mm for a 25-mm thick, LYSO continuous detector using a maximum likelihood position algorithm and shallow slots cut into the entrance surface

Spatial resolution studies of a GEM-TPC

Energy Technology Data Exchange (ETDEWEB)

Berger, Martin [TU Muenchen, 85748 Garching (Germany); Collaboration: GEM-TPC-Collaboration

2015-07-01

A GEM-TPC can exploit the intrinsic suppression of back drifting ions from the amplification stage of the GEM (Gas Electron Multiplier) foils to overcome the problem of drift-field distortions in an ungated operation. To explore the possibility of such a continuously running TPC (Time Projection Chamber) a large-size detector was built. This detector, with a drift length of 728 mm and a radius of 308 mm and a total of 10254 electronic channels, was designed as an upgrade for the FOPI experiment at GSI (Darmstadt, Germany) to improve the secondary vertex resolution especially for K{sup 0}{sub S}- and Λ-reconstruction and the PID capabilities. After commissioning a large statistics of cosmic data and beam-target reactions has been collected and the obtained tracks in the TPC have been used to improve the tracking algorithms. During the track finding and fitting procedure a clustering algorithm which takes into account the track topology as well as the full 3D spatial information is employed. The the clustering algorithm, the cluster error calculation and the tracking resolution are discussed in this contribution.

Super-resolution of facial images in forensics scenarios

DEFF Research Database (Denmark)

Satiro, Joao; Nasrollahi, Kamal; Correia, Paulo

2015-01-01

-resolution (SR) algorithms might be used. But, the problem with these algorithms is that they mostly require motion estimation between LR and low-quality images which is not always practical. To deal with this, we first simply interpolate the LR input images and then perform motion estimation. The estimated...... motion parameters are then used in a non-local mean-based SR algorithm to produce a higher quality image. This image is further fused with the interpolated version of the reference image via an alpha-blending approach. The experimental results on benchmark datasets and locally collected videos from...

Double-Stage Delay Multiply and Sum Beamforming Algorithm: Application to Linear-Array Photoacoustic Imaging

OpenAIRE

Mozaffarzadeh, Moein; Mahloojifar, Ali; Orooji, Mahdi; Adabi, Saba; Nasiriavanaki, Mohammadreza

2018-01-01

Photoacoustic imaging (PAI) is an emerging medical imaging modality capable of providing high spatial resolution of Ultrasound (US) imaging and high contrast of optical imaging. Delay-and-Sum (DAS) is the most common beamforming algorithm in PAI. However, using DAS beamformer leads to low resolution images and considerable contribution of off-axis signals. A new paradigm namely Delay-Multiply-and-Sum (DMAS), which was originally used as a reconstruction algorithm in confocal microwave imaging...

MAPSM: A Spatio-Temporal Algorithm for Merging Soil Moisture from Active and Passive Microwave Remote Sensing

Directory of Open Access Journals (Sweden)

Sat Kumar Tomer

2016-12-01

Full Text Available Availability of soil moisture observations at a high spatial and temporal resolution is a prerequisite for various hydrological, agricultural and meteorological applications. In the current study, a novel algorithm for merging soil moisture from active microwave (SAR and passive microwave is presented. The MAPSM algorithm—Merge Active and Passive microwave Soil Moisture—uses a spatio-temporal approach based on the concept of the Water Change Capacity (WCC which represents the amplitude and direction of change in the soil moisture at the fine spatial resolution. The algorithm is applied and validated during a period of 3 years spanning from 2010 to 2013 over the Berambadi watershed which is located in a semi-arid tropical region in the Karnataka state of south India. Passive microwave products are provided from ESA Level 2 soil moisture products derived from Soil Moisture and Ocean Salinity (SMOS satellite (3 days temporal resolution and 40 km nominal spatial resolution. Active microwave are based on soil moisture retrievals from 30 images of RADARSAT-2 data (24 days temporal resolution and 20 m spatial resolution. The results show that MAPSM is able to provide a good estimate of soil moisture at a spatial resolution of 500 m with an RMSE of 0.025 m3/m3 and 0.069 m3/m3 when comparing it to soil moisture from RADARSAT-2 and in-situ measurements, respectively. The use of Sentinel-1 and RISAT products in MAPSM algorithm is envisioned over other areas where high number of revisits is available. This will need an update of the algorithm to take into account the angle sampling and resolution of Sentinel-1 and RISAT data.

Image reconstruction with shift-variant filtration and its implication for noise and resolution properties in fan-beam computed tomography

International Nuclear Information System (INIS)

Pan Xiaochuan; Yu Lifeng

2003-01-01

In computed tomography (CT), the fan-beam filtered backprojection (FFBP) algorithm is used widely for image reconstruction. It is known that the FFBP algorithm can significantly amplify data noise and aliasing artifacts in situations where the focal lengths are comparable to or smaller than the size of the field of measurement (FOM). In this work, we propose an algorithm that is less susceptible to data noise, aliasing, and other data inconsistencies than is the FFBP algorithm while retaining the favorable resolution properties of the FFBP algorithm. In an attempt to evaluate the noise properties in reconstructed images, we derive analytic expressions for image variances obtained by use of the FFBP algorithm and the proposed algorithm. Computer simulation studies are conducted for quantitative evaluation of the spatial resolution and noise properties of images reconstructed by use of the algorithms. Numerical results of these studies confirm the favorable spatial resolution and noise properties of the proposed algorithm and verify the validity of the theoretically predicted image variances. The proposed algorithm and the derived analytic expressions for image variances can have practical implications for both estimation and detection/classification tasks making use of CT images, and they can readily be generalized to other fan-beam geometries

A multi-resolution approach to heat kernels on discrete surfaces

KAUST Repository

Vaxman, Amir

2010-07-26

Studying the behavior of the heat diffusion process on a manifold is emerging as an important tool for analyzing the geometry of the manifold. Unfortunately, the high complexity of the computation of the heat kernel - the key to the diffusion process - limits this type of analysis to 3D models of modest resolution. We show how to use the unique properties of the heat kernel of a discrete two dimensional manifold to overcome these limitations. Combining a multi-resolution approach with a novel approximation method for the heat kernel at short times results in an efficient and robust algorithm for computing the heat kernels of detailed models. We show experimentally that our method can achieve good approximations in a fraction of the time required by traditional algorithms. Finally, we demonstrate how these heat kernels can be used to improve a diffusion-based feature extraction algorithm. © 2010 ACM.

Multi-resolution inversion algorithm for the attenuated radon transform

KAUST Repository

Barbano, Paolo Emilio

2011-09-01

We present a FAST implementation of the Inverse Attenuated Radon Transform which incorporates accurate collimator response, as well as artifact rejection due to statistical noise and data corruption. This new reconstruction procedure is performed by combining a memory-efficient implementation of the analytical inversion formula (AIF [1], [2]) with a wavelet-based version of a recently discovered regularization technique [3]. The paper introduces all the main aspects of the new AIF, as well numerical experiments on real and simulated data. Those display a substantial improvement in reconstruction quality when compared to linear or iterative algorithms. © 2011 IEEE.

EVALUATION OF WEB SEARCHING METHOD USING A NOVEL WPRR ALGORITHM FOR TWO DIFFERENT CASE STUDIES

Directory of Open Access Journals (Sweden)

V. Lakshmi Praba

2012-04-01

Full Text Available The World-Wide Web provides every internet citizen with access to an abundance of information, but it becomes increasingly difficult to identify the relevant pieces of information. Research in web mining tries to address this problem by applying techniques from data mining and machine learning to web data and documents. Web content mining and web structure mining have important roles in identifying the relevant web page. Relevancy of web page denotes how well a retrieved web page or set of web pages meets the information need of the user. Page Rank, Weighted Page Rank and Hypertext Induced Topic Selection (HITS are existing algorithms which considers only web structure mining. Vector Space Model (VSM, Cover Density Ranking (CDR, Okapi similarity measurement (Okapi and Three-Level Scoring method (TLS are some of existing relevancy score methods which consider only web content mining. In this paper, we propose a new algorithm, Weighted Page with Relevant Rank (WPRR which is blend of both web content mining and web structure mining that demonstrates the relevancy of the page with respect to given query for two different case scenarios. It is shown that WPRR’s performance is better than the existing algorithms.

Estimating reaction rate constants: comparison between traditional curve fitting and curve resolution

NARCIS (Netherlands)

Bijlsma, S.; Boelens, H. F. M.; Hoefsloot, H. C. J.; Smilde, A. K.

2000-01-01

A traditional curve fitting (TCF) algorithm is compared with a classical curve resolution (CCR) approach for estimating reaction rate constants from spectral data obtained in time of a chemical reaction. In the TCF algorithm, reaction rate constants an estimated from the absorbance versus time data

A cloud masking algorithm for EARLINET lidar systems

Science.gov (United States)

Binietoglou, Ioannis; Baars, Holger; D'Amico, Giuseppe; Nicolae, Doina

2015-04-01

Cloud masking is an important first step in any aerosol lidar processing chain as most data processing algorithms can only be applied on cloud free observations. Up to now, the selection of a cloud-free time interval for data processing is typically performed manually, and this is one of the outstanding problems for automatic processing of lidar data in networks such as EARLINET. In this contribution we present initial developments of a cloud masking algorithm that permits the selection of the appropriate time intervals for lidar data processing based on uncalibrated lidar signals. The algorithm is based on a signal normalization procedure using the range of observed values of lidar returns, designed to work with different lidar systems with minimal user input. This normalization procedure can be applied to measurement periods of only few hours, even if no suitable cloud-free interval exists, and thus can be used even when only a short period of lidar measurements is available. Clouds are detected based on a combination of criteria including the magnitude of the normalized lidar signal and time-space edge detection performed using the Sobel operator. In this way the algorithm avoids misclassification of strong aerosol layers as clouds. Cloud detection is performed using the highest available time and vertical resolution of the lidar signals, allowing the effective detection of low-level clouds (e.g. cumulus humilis). Special attention is given to suppress false cloud detection due to signal noise that can affect the algorithm's performance, especially during day-time. In this contribution we present the details of algorithm, the effect of lidar characteristics (space-time resolution, available wavelengths, signal-to-noise ratio) to detection performance, and highlight the current strengths and limitations of the algorithm using lidar scenes from different lidar systems in different locations across Europe.

Level-0 trigger algorithms for the ALICE PHOS detector

CERN Document Server

Wang, D; Wang, Y P; Huang, G M; Kral, J; Yin, Z B; Zhou, D C; Zhang, F; Ullaland, K; Muller, H; Liu, L J

2011-01-01

The PHOS level-0 trigger provides a minimum bias trigger for p-p collisions and information for a level-1 trigger at both p-p and Pb-Pb collisions. There are two level-0 trigger generating algorithms under consideration: the Direct Comparison algorithm and the Weighted Sum algorithm. In order to study trigger algorithms via simulation, a simplified equivalent model is extracted from the trigger electronics to derive the waveform function of the Analog-or signal as input to the trigger algorithms. Simulations shown that the Weighted Sum algorithm can achieve higher trigger efficiency and provide more precise single channel energy information than the direct compare algorithm. An energy resolution of 9.75 MeV can be achieved with the Weighted Sum algorithm at a sampling rate of 40 Msps (mega samples per second) at 1 GeV. The timing performance at a sampling rate of 40 Msps with the Weighted Sum algorithm is better than that at a sampling rate of 20 Msps with both algorithms. The level-0 trigger can be delivered...

High resolution integral holography using Fourier ptychographic approach.

Science.gov (United States)

Li, Zhaohui; Zhang, Jianqi; Wang, Xiaorui; Liu, Delian

2014-12-29

An innovative approach is proposed for calculating high resolution computer generated integral holograms by using the Fourier Ptychographic (FP) algorithm. The approach initializes a high resolution complex hologram with a random guess, and then stitches together low resolution multi-view images, synthesized from the elemental images captured by integral imaging (II), to recover the high resolution hologram through an iterative retrieval with FP constrains. This paper begins with an analysis of the principle of hologram synthesis from multi-projections, followed by an accurate determination of the constrains required in the Fourier ptychographic integral-holography (FPIH). Next, the procedure of the approach is described in detail. Finally, optical reconstructions are performed and the results are demonstrated. Theoretical analysis and experiments show that our proposed approach can reconstruct 3D scenes with high resolution.

Resolution enhancement of lung 4D-CT data using multiscale interphase iterative nonlocal means

International Nuclear Information System (INIS)

Zhang Yu; Yap, Pew-Thian; Wu Guorong; Feng Qianjin; Chen Wufan; Lian Jun; Shen Dinggang

2013-01-01

Purpose: Four-dimensional computer tomography (4D-CT) has been widely used in lung cancer radiotherapy due to its capability in providing important tumor motion information. However, the prolonged scanning duration required by 4D-CT causes considerable increase in radiation dose. To minimize the radiation-related health risk, radiation dose is often reduced at the expense of interslice spatial resolution. However, inadequate resolution in 4D-CT causes artifacts and increases uncertainty in tumor localization, which eventually results in extra damages of healthy tissues during radiotherapy. In this paper, the authors propose a novel postprocessing algorithm to enhance the resolution of lung 4D-CT data. Methods: The authors' premise is that anatomical information missing in one phase can be recovered from the complementary information embedded in other phases. The authors employ a patch-based mechanism to propagate information across phases for the reconstruction of intermediate slices in the longitudinal direction, where resolution is normally the lowest. Specifically, the structurally matching and spatially nearby patches are combined for reconstruction of each patch. For greater sensitivity to anatomical details, the authors employ a quad-tree technique to adaptively partition the image for more fine-grained refinement. The authors further devise an iterative strategy for significant enhancement of anatomical details. Results: The authors evaluated their algorithm using a publicly available lung data that consist of 10 4D-CT cases. The authors’ algorithm gives very promising results with significantly enhanced image structures and much less artifacts. Quantitative analysis shows that the authors’ algorithm increases peak signal-to-noise ratio by 3–4 dB and the structural similarity index by 3%–5% when compared with the standard interpolation-based algorithms. Conclusions: The authors have developed a new algorithm to improve the resolution of 4D-CT. It

Two-energy twin image removal in atomic-resolution x-ray holography

International Nuclear Information System (INIS)

Nishino, Y.; Ishikawa, T.; Hayashi, K.; Takahashi, Y.; Matsubara, E.

2002-01-01

We propose a two-energy twin image removal algorithm for atomic-resolution x-ray holography. The validity of the algorithm is shown in a theoretical simulation and in an experiment of internal detector x-ray holography using a ZnSe single crystal. The algorithm, compared to the widely used multiple-energy algorithm, allows efficient measurement of holograms, and is especially important when the available x-ray energies are fixed. It enables twin image free holography using characteristic x rays from laboratory generators and x-ray pulses of free-electron lasers

Intra-and-Inter Species Biomass Prediction in a Plantation Forest: Testing the Utility of High Spatial Resolution Spaceborne Multispectral RapidEye Sensor and Advanced Machine Learning Algorithms

Directory of Open Access Journals (Sweden)

Timothy Dube

2014-08-01

Full Text Available The quantification of aboveground biomass using remote sensing is critical for better understanding the role of forests in carbon sequestration and for informed sustainable management. Although remote sensing techniques have been proven useful in assessing forest biomass in general, more is required to investigate their capabilities in predicting intra-and-inter species biomass which are mainly characterised by non-linear relationships. In this study, we tested two machine learning algorithms, Stochastic Gradient Boosting (SGB and Random Forest (RF regression trees to predict intra-and-inter species biomass using high resolution RapidEye reflectance bands as well as the derived vegetation indices in a commercial plantation. The results showed that the SGB algorithm yielded the best performance for intra-and-inter species biomass prediction; using all the predictor variables as well as based on the most important selected variables. For example using the most important variables the algorithm produced an R2 of 0.80 and RMSE of 16.93 t·ha−1 for E. grandis; R2 of 0.79, RMSE of 17.27 t·ha−1 for P. taeda and R2 of 0.61, RMSE of 43.39 t·ha−1 for the combined species data sets. Comparatively, RF yielded plausible results only for E. dunii (R2 of 0.79; RMSE of 7.18 t·ha−1. We demonstrated that although the two statistical methods were able to predict biomass accurately, RF produced weaker results as compared to SGB when applied to combined species dataset. The result underscores the relevance of stochastic models in predicting biomass drawn from different species and genera using the new generation high resolution RapidEye sensor with strategically positioned bands.

Optimal image resolution for digital storage of radiotherapy-planning images

International Nuclear Information System (INIS)

Baba, Yuji; Furusawa, Mitsuhiro; Murakami, Ryuji; Baba, Takashi; Yokoyama, Toshimi; Nishimura, Ryuichi; Takahashi, Mutsumasa

1998-01-01

Purpose: To evaluate the quality of digitized radiation-planning images at different resolution and to determine the optimal resolution for digital storage. Methods and Materials: Twenty-five planning films were scanned and digitized using a film scanner at a resolution of 72 dots per inch (dpi) with 8-bit depth. The resolution of scanned images was reduced to 48, 36, 24, and 18 dpi using computer software. Image qualities of these five images (72, 48, 36, 24, and 18 dpi) were evaluated and given scores (4 = excellent; 3 = good; 2 = fair; and 1 = poor) by three radiation oncologists. An image data compression algorithm by the Joint Photographic Experts Group (JPEG) (not reversible and some information will be lost) was also evaluated. Results: The scores of digitized images with 72, 48, 36, 24, and 17 dpi resolution were 3.8 ± 0.3, 3.5 ± 0.3, 3.3 ± 0.5, 2.7 ± 0.5, and 1.6 ± 0.3, respectively. The quality of 36-dpi images were definitely worse compared to 72-dpi images, but were good enough as planning films. Digitized planning images with 72- and 36-dpi resolution requires about 800 and 200 KBytes, respectively. The JPEG compression algorithm produces little degradation in 36-dpi images at compression ratios of 5:1. Conclusion: The quality of digitized images with 36-dpi resolution was good enough as radiation-planning images and required 200 KBytes/image

The performance of the new enhanced-resolution satellite passive microwave dataset applied for snow water equivalent estimation

Science.gov (United States)

Pan, J.; Durand, M. T.; Jiang, L.; Liu, D.

2017-12-01

The newly-processed NASA MEaSures Calibrated Enhanced-Resolution Brightness Temperature (CETB) reconstructed using antenna measurement response function (MRF) is considered to have significantly improved fine-resolution measurements with better georegistration for time-series observations and equivalent field of view (FOV) for frequencies with the same monomial spatial resolution. We are looking forward to its potential for the global snow observing purposes, and therefore aim to test its performance for characterizing snow properties, especially the snow water equivalent (SWE) in large areas. In this research, two candidate SWE algorithms will be tested in China for the years between 2005 to 2010 using the reprocessed TB from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E), with the results to be evaluated using the daily snow depth measurements at over 700 national synoptic stations. One of the algorithms is the SWE retrieval algorithm used for the FengYun (FY) - 3 Microwave Radiation Imager. This algorithm uses the multi-channel TB to calculate SWE for three major snow regions in China, with the coefficients adapted for different land cover types. The second algorithm is the newly-established Bayesian Algorithm for SWE Estimation with Passive Microwave measurements (BASE-PM). This algorithm uses the physically-based snow radiative transfer model to find the histogram of most-likely snow property that matches the multi-frequency TB from 10.65 to 90 GHz. It provides a rough estimation of snow depth and grain size at the same time and showed a 30 mm SWE RMS error using the ground radiometer measurements at Sodankyla. This study will be the first attempt to test it spatially for satellite. The use of this algorithm benefits from the high resolution and the spatial consistency between frequencies embedded in the new dataset. This research will answer three questions. First, to what extent can CETB increase the heterogeneity in the mapped SWE? Second, will

Linear-Array Photoacoustic Imaging Using Minimum Variance-Based Delay Multiply and Sum Adaptive Beamforming Algorithm

OpenAIRE

Mozaffarzadeh, Moein; Mahloojifar, Ali; Orooji, Mahdi; Kratkiewicz, Karl; Adabi, Saba; Nasiriavanaki, Mohammadreza

2017-01-01

In Photoacoustic imaging (PA), Delay-and-Sum (DAS) beamformer is a common beamforming algorithm having a simple implementation. However, it results in a poor resolution and high sidelobes. To address these challenges, a new algorithm namely Delay-Multiply-and-Sum (DMAS) was introduced having lower sidelobes compared to DAS. To improve the resolution of DMAS, a novel beamformer is introduced using Minimum Variance (MV) adaptive beamforming combined with DMAS, so-called Minimum Variance-Based D...

Studies of high resolution array processing algorithms for multibeam bathymetric applications

Digital Repository Service at National Institute of Oceanography (India)

Chakraborty, B.; Schenke, H.W.

In this paper a study is initiated to observe the usefulness of directional spectral estimation techniques for underwater bathymetric applications. High resolution techniques like the Maximum Likelihood (ML) method and the Maximum Entropy (ME...

Motion tolerant iterative reconstruction algorithm for cone-beam helical CT imaging

Energy Technology Data Exchange (ETDEWEB)

Takahashi, Hisashi; Goto, Taiga; Hirokawa, Koichi; Miyazaki, Osamu [Hitachi Medical Corporation, Chiba-ken (Japan). CT System Div.

2011-07-01

We have developed a new advanced iterative reconstruction algorithm for cone-beam helical CT. The features of this algorithm are: (a) it uses separable paraboloidal surrogate (SPS) technique as a foundation for reconstruction to reduce noise and cone-beam artifact, (b) it uses a view weight in the back-projection process to reduce motion artifact. To confirm the improvement of our proposed algorithm over other existing algorithm, such as Feldkamp-Davis-Kress (FDK) or SPS algorithm, we compared the motion artifact reduction, image noise reduction (standard deviation of CT number), and cone-beam artifact reduction on simulated and clinical data set. Our results demonstrate that the proposed algorithm dramatically reduces motion artifacts compared with the SPS algorithm, and decreases image noise compared with the FDK algorithm. In addition, the proposed algorithm potentially improves time resolution of iterative reconstruction. (orig.)

A maximum-likelihood reconstruction algorithm for tomographic gamma-ray nondestructive assay

International Nuclear Information System (INIS)

Prettyman, T.H.; Estep, R.J.; Cole, R.A.; Sheppard, G.A.

1994-01-01

A new tomographic reconstruction algorithm for nondestructive assay with high resolution gamma-ray spectroscopy (HRGS) is presented. The reconstruction problem is formulated using a maximum-likelihood approach in which the statistical structure of both the gross and continuum measurements used to determine the full-energy response in HRGS is precisely modeled. An accelerated expectation-maximization algorithm is used to determine the optimal solution. The algorithm is applied to safeguards and environmental assays of large samples (for example, 55-gal. drums) in which high continuum levels caused by Compton scattering are routinely encountered. Details of the implementation of the algorithm and a comparative study of the algorithm's performance are presented

An Enhanced TIMESAT Algorithm for Estimating Vegetation Phenology Metrics from MODIS Data

Science.gov (United States)

Tan, Bin; Morisette, Jeffrey T.; Wolfe, Robert E.; Gao, Feng; Ederer, Gregory A.; Nightingale, Joanne; Pedelty, Jeffrey A.

2012-01-01

An enhanced TIMESAT algorithm was developed for retrieving vegetation phenology metrics from 250 m and 500 m spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indexes (VI) over North America. MODIS VI data were pre-processed using snow-cover and land surface temperature data, and temporally smoothed with the enhanced TIMESAT algorithm. An objective third derivative test was applied to define key phenology dates and retrieve a set of phenology metrics. This algorithm has been applied to two MODIS VIs: Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). In this paper, we describe the algorithm and use EVI as an example to compare three sets of TIMESAT algorithm/MODIS VI combinations: a) original TIMESAT algorithm with original MODIS VI, b) original TIMESAT algorithm with pre-processed MODIS VI, and c) enhanced TIMESAT and pre-processed MODIS VI. All retrievals were compared with ground phenology observations, some made available through the National Phenology Network. Our results show that for MODIS data in middle to high latitude regions, snow and land surface temperature information is critical in retrieving phenology metrics from satellite observations. The results also show that the enhanced TIMESAT algorithm can better accommodate growing season start and end dates that vary significantly from year to year. The TIMESAT algorithm improvements contribute to more spatial coverage and more accurate retrievals of the phenology metrics. Among three sets of TIMESAT/MODIS VI combinations, the start of the growing season metric predicted by the enhanced TIMESAT algorithm using pre-processed MODIS VIs has the best associations with ground observed vegetation greenup dates.

Multisensor Super Resolution Using Directionally-Adaptive Regularization for UAV Images.

Science.gov (United States)

Kang, Wonseok; Yu, Soohwan; Ko, Seungyong; Paik, Joonki

2015-05-22

In various unmanned aerial vehicle (UAV) imaging applications, the multisensor super-resolution (SR) technique has become a chronic problem and attracted increasing attention. Multisensor SR algorithms utilize multispectral low-resolution (LR) images to make a higher resolution (HR) image to improve the performance of the UAV imaging system. The primary objective of the paper is to develop a multisensor SR method based on the existing multispectral imaging framework instead of using additional sensors. In order to restore image details without noise amplification or unnatural post-processing artifacts, this paper presents an improved regularized SR algorithm by combining the directionally-adaptive constraints and multiscale non-local means (NLM) filter. As a result, the proposed method can overcome the physical limitation of multispectral sensors by estimating the color HR image from a set of multispectral LR images using intensity-hue-saturation (IHS) image fusion. Experimental results show that the proposed method provides better SR results than existing state-of-the-art SR methods in the sense of objective measures.

Anatomy assisted PET image reconstruction incorporating multi-resolution joint entropy

International Nuclear Information System (INIS)

Tang, Jing; Rahmim, Arman

2015-01-01

A promising approach in PET image reconstruction is to incorporate high resolution anatomical information (measured from MR or CT) taking the anato-functional similarity measures such as mutual information or joint entropy (JE) as the prior. These similarity measures only classify voxels based on intensity values, while neglecting structural spatial information. In this work, we developed an anatomy-assisted maximum a posteriori (MAP) reconstruction algorithm wherein the JE measure is supplied by spatial information generated using wavelet multi-resolution analysis. The proposed wavelet-based JE (WJE) MAP algorithm involves calculation of derivatives of the subband JE measures with respect to individual PET image voxel intensities, which we have shown can be computed very similarly to how the inverse wavelet transform is implemented. We performed a simulation study with the BrainWeb phantom creating PET data corresponding to different noise levels. Realistically simulated T1-weighted MR images provided by BrainWeb modeling were applied in the anatomy-assisted reconstruction with the WJE-MAP algorithm and the intensity-only JE-MAP algorithm. Quantitative analysis showed that the WJE-MAP algorithm performed similarly to the JE-MAP algorithm at low noise level in the gray matter (GM) and white matter (WM) regions in terms of noise versus bias tradeoff. When noise increased to medium level in the simulated data, the WJE-MAP algorithm started to surpass the JE-MAP algorithm in the GM region, which is less uniform with smaller isolated structures compared to the WM region. In the high noise level simulation, the WJE-MAP algorithm presented clear improvement over the JE-MAP algorithm in both the GM and WM regions. In addition to the simulation study, we applied the reconstruction algorithms to real patient studies involving DPA-173 PET data and Florbetapir PET data with corresponding T1-MPRAGE MRI images. Compared to the intensity-only JE-MAP algorithm, the WJE

Anatomy assisted PET image reconstruction incorporating multi-resolution joint entropy

Science.gov (United States)

Tang, Jing; Rahmim, Arman

2015-01-01

A promising approach in PET image reconstruction is to incorporate high resolution anatomical information (measured from MR or CT) taking the anato-functional similarity measures such as mutual information or joint entropy (JE) as the prior. These similarity measures only classify voxels based on intensity values, while neglecting structural spatial information. In this work, we developed an anatomy-assisted maximum a posteriori (MAP) reconstruction algorithm wherein the JE measure is supplied by spatial information generated using wavelet multi-resolution analysis. The proposed wavelet-based JE (WJE) MAP algorithm involves calculation of derivatives of the subband JE measures with respect to individual PET image voxel intensities, which we have shown can be computed very similarly to how the inverse wavelet transform is implemented. We performed a simulation study with the BrainWeb phantom creating PET data corresponding to different noise levels. Realistically simulated T1-weighted MR images provided by BrainWeb modeling were applied in the anatomy-assisted reconstruction with the WJE-MAP algorithm and the intensity-only JE-MAP algorithm. Quantitative analysis showed that the WJE-MAP algorithm performed similarly to the JE-MAP algorithm at low noise level in the gray matter (GM) and white matter (WM) regions in terms of noise versus bias tradeoff. When noise increased to medium level in the simulated data, the WJE-MAP algorithm started to surpass the JE-MAP algorithm in the GM region, which is less uniform with smaller isolated structures compared to the WM region. In the high noise level simulation, the WJE-MAP algorithm presented clear improvement over the JE-MAP algorithm in both the GM and WM regions. In addition to the simulation study, we applied the reconstruction algorithms to real patient studies involving DPA-173 PET data and Florbetapir PET data with corresponding T1-MPRAGE MRI images. Compared to the intensity-only JE-MAP algorithm, the WJE

Restoration and Super-Resolution of Diffraction-Limited Imagery Data by Bayesian and Set-Theoretic Approaches

National Research Council Canada - National Science Library

Sundareshan, Malur

2001-01-01

This project was primarily aimed at the design of novel algorithms for the restoration and super-resolution processing of imagery data to improve the resolution in images acquired from practical sensing operations...

Super-resolution for scanning light stimulation systems

Energy Technology Data Exchange (ETDEWEB)

Bitzer, L. A.; Neumann, K.; Benson, N., E-mail: niels.benson@uni-due.de; Schmechel, R. [Faculty of Engineering, NST and CENIDE, University of Duisburg-Essen, Bismarckstr. 81, 47057 Duisburg (Germany)

2016-09-15

Super-resolution (SR) is a technique used in digital image processing to overcome the resolution limitation of imaging systems. In this process, a single high resolution image is reconstructed from multiple low resolution images. SR is commonly used for CCD and CMOS (Complementary Metal-Oxide-Semiconductor) sensor images, as well as for medical applications, e.g., magnetic resonance imaging. Here, we demonstrate that super-resolution can be applied with scanning light stimulation (LS) systems, which are common to obtain space-resolved electro-optical parameters of a sample. For our purposes, the Projection Onto Convex Sets (POCS) was chosen and modified to suit the needs of LS systems. To demonstrate the SR adaption, an Optical Beam Induced Current (OBIC) LS system was used. The POCS algorithm was optimized by means of OBIC short circuit current measurements on a multicrystalline solar cell, resulting in a mean square error reduction of up to 61% and improved image quality.

Accurate 3D reconstruction by a new PDS-OSEM algorithm for HRRT

International Nuclear Information System (INIS)

Chen, Tai-Been; Horng-Shing Lu, Henry; Kim, Hang-Keun; Son, Young-Don; Cho, Zang- Hee

2014-01-01

State-of-the-art high resolution research tomography (HRRT) provides high resolution PET images with full 3D human brain scanning. But, a short time frame in dynamic study causes many problems related to the low counts in the acquired data. The PDS-OSEM algorithm was proposed to reconstruct the HRRT image with a high signal-to-noise ratio that provides accurate information for dynamic data. The new algorithm was evaluated by simulated image, empirical phantoms, and real human brain data. Meanwhile, the time activity curve was adopted to validate a reconstructed performance of dynamic data between PDS-OSEM and OP-OSEM algorithms. According to simulated and empirical studies, the PDS-OSEM algorithm reconstructs images with higher quality, higher accuracy, less noise, and less average sum of square error than those of OP-OSEM. The presented algorithm is useful to provide quality images under the condition of low count rates in dynamic studies with a short scan time. - Highlights: • The PDS-OSEM reconstructs PET images with iteratively compensating random and scatter corrections from prompt sinogram. • The PDS-OSEM can reconstruct PET images with low count data and data contaminations. • The PDS-OSEM provides less noise and higher quality of reconstructed images than those of OP-OSEM algorithm in statistical sense

Sparse spectral deconvolution algorithm for noncartesian MR spectroscopic imaging.

Science.gov (United States)

Bhave, Sampada; Eslami, Ramin; Jacob, Mathews

2014-02-01

To minimize line shape distortions and spectral leakage artifacts in MR spectroscopic imaging (MRSI). A spatially and spectrally regularized non-Cartesian MRSI algorithm that uses the line shape distortion priors, estimated from water reference data, to deconvolve the spectra is introduced. Sparse spectral regularization is used to minimize noise amplification associated with deconvolution. A spiral MRSI sequence that heavily oversamples the central k-space regions is used to acquire the MRSI data. The spatial regularization term uses the spatial supports of brain and extracranial fat regions to recover the metabolite spectra and nuisance signals at two different resolutions. Specifically, the nuisance signals are recovered at the maximum resolution to minimize spectral leakage, while the point spread functions of metabolites are controlled to obtain acceptable signal-to-noise ratio. The comparisons of the algorithm against Tikhonov regularized reconstructions demonstrates considerably reduced line-shape distortions and improved metabolite maps. The proposed sparsity constrained spectral deconvolution scheme is effective in minimizing the line-shape distortions. The dual resolution reconstruction scheme is capable of minimizing spectral leakage artifacts. Copyright © 2013 Wiley Periodicals, Inc.

ALTERNATIVE DISPUTE RESOLUTION IN BANYUMAS REGENCY: IN THE PERSPECTIVE OF CULTURAL STUDIES

Directory of Open Access Journals (Sweden)

Singkir Hudijono

2012-11-01

mechanism in deconstructing the law centralism because it can beimplemented effectively and efficiently, and ensures the win-win solution. Thirdly,denotatively, the alternative dispute solution reduces the confronting and antagonisticconceptions. Connotatively, the alternative dispute resolution is the legal culture ofBanyumas society. It has functioned as the legal dynamisator creating and implementinglaw.

A novel fast phase correlation algorithm for peak wavelength detection of Fiber Bragg Grating sensors.

Science.gov (United States)

Lamberti, A; Vanlanduit, S; De Pauw, B; Berghmans, F

2014-03-24

Fiber Bragg Gratings (FBGs) can be used as sensors for strain, temperature and pressure measurements. For this purpose, the ability to determine the Bragg peak wavelength with adequate wavelength resolution and accuracy is essential. However, conventional peak detection techniques, such as the maximum detection algorithm, can yield inaccurate and imprecise results, especially when the Signal to Noise Ratio (SNR) and the wavelength resolution are poor. Other techniques, such as the cross-correlation demodulation algorithm are more precise and accurate but require a considerable higher computational effort. To overcome these problems, we developed a novel fast phase correlation (FPC) peak detection algorithm, which computes the wavelength shift in the reflected spectrum of a FBG sensor. This paper analyzes the performance of the FPC algorithm for different values of the SNR and wavelength resolution. Using simulations and experiments, we compared the FPC with the maximum detection and cross-correlation algorithms. The FPC method demonstrated a detection precision and accuracy comparable with those of cross-correlation demodulation and considerably higher than those obtained with the maximum detection technique. Additionally, FPC showed to be about 50 times faster than the cross-correlation. It is therefore a promising tool for future implementation in real-time systems or in embedded hardware intended for FBG sensor interrogation.

Development of MODIS data-based algorithm for retrieving sea surface temperature in coastal waters.

Science.gov (United States)

Wang, Jiao; Deng, Zhiqiang

2017-06-01

A new algorithm was developed for retrieving sea surface temperature (SST) in coastal waters using satellite remote sensing data from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua platform. The new SST algorithm was trained using the Artificial Neural Network (ANN) method and tested using 8 years of remote sensing data from MODIS Aqua sensor and in situ sensing data from the US coastal waters in Louisiana, Texas, Florida, California, and New Jersey. The ANN algorithm could be utilized to map SST in both deep offshore and particularly shallow nearshore waters at the high spatial resolution of 1 km, greatly expanding the coverage of remote sensing-based SST data from offshore waters to nearshore waters. Applications of the ANN algorithm require only the remotely sensed reflectance values from the two MODIS Aqua thermal bands 31 and 32 as input data. Application results indicated that the ANN algorithm was able to explaining 82-90% variations in observed SST in US coastal waters. While the algorithm is generally applicable to the retrieval of SST, it works best for nearshore waters where important coastal resources are located and existing algorithms are either not applicable or do not work well, making the new ANN-based SST algorithm unique and particularly useful to coastal resource management.

Comparison between iterative wavefront control algorithm and direct gradient wavefront control algorithm for adaptive optics system

Science.gov (United States)

Cheng, Sheng-Yi; Liu, Wen-Jin; Chen, Shan-Qiu; Dong, Li-Zhi; Yang, Ping; Xu, Bing

2015-08-01

Among all kinds of wavefront control algorithms in adaptive optics systems, the direct gradient wavefront control algorithm is the most widespread and common method. This control algorithm obtains the actuator voltages directly from wavefront slopes through pre-measuring the relational matrix between deformable mirror actuators and Hartmann wavefront sensor with perfect real-time characteristic and stability. However, with increasing the number of sub-apertures in wavefront sensor and deformable mirror actuators of adaptive optics systems, the matrix operation in direct gradient algorithm takes too much time, which becomes a major factor influencing control effect of adaptive optics systems. In this paper we apply an iterative wavefront control algorithm to high-resolution adaptive optics systems, in which the voltages of each actuator are obtained through iteration arithmetic, which gains great advantage in calculation and storage. For AO system with thousands of actuators, the computational complexity estimate is about O(n2) ˜ O(n3) in direct gradient wavefront control algorithm, while the computational complexity estimate in iterative wavefront control algorithm is about O(n) ˜ (O(n)3/2), in which n is the number of actuators of AO system. And the more the numbers of sub-apertures and deformable mirror actuators, the more significant advantage the iterative wavefront control algorithm exhibits. Project supported by the National Key Scientific and Research Equipment Development Project of China (Grant No. ZDYZ2013-2), the National Natural Science Foundation of China (Grant No. 11173008), and the Sichuan Provincial Outstanding Youth Academic Technology Leaders Program, China (Grant No. 2012JQ0012).

Speckle correlation resolution enhancement of wide-field fluorescence imaging (Conference Presentation)

Science.gov (United States)

Yilmaz, Hasan

2016-03-01

Structured illumination enables high-resolution fluorescence imaging of nanostructures [1]. We demonstrate a new high-resolution fluorescence imaging method that uses a scattering layer with a high-index substrate as a solid immersion lens [2]. Random scattering of coherent light enables a speckle pattern with a very fine structure that illuminates the fluorescent nanospheres on the back surface of the high-index substrate. The speckle pattern is raster-scanned over the fluorescent nanospheres using a speckle correlation effect known as the optical memory effect. A series of standard-resolution fluorescence images per each speckle pattern displacement are recorded by an electron-multiplying CCD camera using a commercial microscope objective. We have developed a new phase-retrieval algorithm to reconstruct a high-resolution, wide-field image from several standard-resolution wide-field images. We have introduced phase information of Fourier components of standard-resolution images as a new constraint in our algorithm which discards ambiguities therefore ensures convergence to a unique solution. We demonstrate two-dimensional fluorescence images of a collection of nanospheres with a deconvolved Abbe resolution of 116 nm and a field of view of 10 µm × 10 µm. Our method is robust against optical aberrations and stage drifts, therefore excellent for imaging nanostructures under ambient conditions. [1] M. G. L. Gustafsson, J. Microsc. 198, 82-87 (2000). [2] H. Yilmaz, E. G. van Putten, J. Bertolotti, A. Lagendijk, W. L. Vos, and A. P. Mosk, Optica 2, 424-429 (2015).

Semi-automatic mapping of linear-trending bedforms using 'Self-Organizing Maps' algorithm

Science.gov (United States)

Foroutan, M.; Zimbelman, J. R.

2017-09-01

Increased application of high resolution spatial data such as high resolution satellite or Unmanned Aerial Vehicle (UAV) images from Earth, as well as High Resolution Imaging Science Experiment (HiRISE) images from Mars, makes it necessary to increase automation techniques capable of extracting detailed geomorphologic elements from such large data sets. Model validation by repeated images in environmental management studies such as climate-related changes as well as increasing access to high-resolution satellite images underline the demand for detailed automatic image-processing techniques in remote sensing. This study presents a methodology based on an unsupervised Artificial Neural Network (ANN) algorithm, known as Self Organizing Maps (SOM), to achieve the semi-automatic extraction of linear features with small footprints on satellite images. SOM is based on competitive learning and is efficient for handling huge data sets. We applied the SOM algorithm to high resolution satellite images of Earth and Mars (Quickbird, Worldview and HiRISE) in order to facilitate and speed up image analysis along with the improvement of the accuracy of results. About 98% overall accuracy and 0.001 quantization error in the recognition of small linear-trending bedforms demonstrate a promising framework.

In Vivo EPR Resolution Enhancement Using Techniques Known from Quantum Computing Spin Technology.

Science.gov (United States)

Rahimi, Robabeh; Halpern, Howard J; Takui, Takeji

2017-01-01

A crucial issue with in vivo biological/medical EPR is its low signal-to-noise ratio, giving rise to the low spectroscopic resolution. We propose quantum hyperpolarization techniques based on 'Heat Bath Algorithmic Cooling', allowing possible approaches for improving the resolution in magnetic resonance spectroscopy and imaging.

A Modularity Degree Based Heuristic Community Detection Algorithm

Directory of Open Access Journals (Sweden)

Dongming Chen

2014-01-01

Full Text Available A community in a complex network can be seen as a subgroup of nodes that are densely connected. Discovery of community structures is a basic problem of research and can be used in various areas, such as biology, computer science, and sociology. Existing community detection methods usually try to expand or collapse the nodes partitions in order to optimize a given quality function. These optimization function based methods share the same drawback of inefficiency. Here we propose a heuristic algorithm (MDBH algorithm based on network structure which employs modularity degree as a measure function. Experiments on both synthetic benchmarks and real-world networks show that our algorithm gives competitive accuracy with previous modularity optimization methods, even though it has less computational complexity. Furthermore, due to the use of modularity degree, our algorithm naturally improves the resolution limit in community detection.

Double-resolution electron holography with simple Fourier transform of fringe-shifted holograms.

Science.gov (United States)

Volkov, V V; Han, M G; Zhu, Y

2013-11-01

We propose a fringe-shifting holographic method with an appropriate image wave recovery algorithm leading to exact solution of holographic equations. With this new method the complex object image wave recovered from holograms appears to have much less traditional artifacts caused by the autocorrelation band present practically in all Fourier transformed holograms. The new analytical solutions make possible a double-resolution electron holography free from autocorrelation band artifacts and thus push the limits for phase resolution. The new image wave recovery algorithm uses a popular Fourier solution of the side band-pass filter technique, while the fringe-shifting holographic method is simple to implement in practice. Published by Elsevier B.V.

Gossip Consensus Algorithm Based on Time-Varying Influence Factors and Weakly Connected Graph for Opinion Evolution in Social Networks

Directory of Open Access Journals (Sweden)

Lingyun Li

2013-01-01

Full Text Available We provide a new gossip algorithm to investigate the problem of opinion consensus with the time-varying influence factors and weakly connected graph among multiple agents. What is more, we discuss not only the effect of the time-varying factors and the randomized topological structure but also the spread of misinformation and communication constrains described by probabilistic quantized communication in the social network. Under the underlying weakly connected graph, we first denote that all opinion states converge to a stochastic consensus almost surely; that is, our algorithm indeed achieves the consensus with probability one. Furthermore, our results show that the mean of all the opinion states converges to the average of the initial states when time-varying influence factors satisfy some conditions. Finally, we give a result about the square mean error between the dynamic opinion states and the benchmark without quantized communication.

Fast centroid algorithm for determining the surface plasmon resonance angle using the fixed-boundary method

International Nuclear Information System (INIS)

Zhan, Shuyue; Wang, Xiaoping; Liu, Yuling

2011-01-01

To simplify the algorithm for determining the surface plasmon resonance (SPR) angle for special applications and development trends, a fast method for determining an SPR angle, called the fixed-boundary centroid algorithm, has been proposed. Two experiments were conducted to compare three centroid algorithms from the aspects of the operation time, sensitivity to shot noise, signal-to-noise ratio (SNR), resolution, and measurement range. Although the measurement range of this method was narrower, the other performance indices were all better than the other two centroid methods. This method has outstanding performance, high speed, good conformity, low error and a high SNR and resolution. It thus has the potential to be widely adopted

MUSIC electromagnetic imaging with enhanced resolution for small inclusions

International Nuclear Information System (INIS)

Chen Xudong; Zhong Yu

2009-01-01

This paper investigates the influence of the test dipole on the resolution of the multiple signal classification (MUSIC) imaging method applied to the electromagnetic inverse scattering problem of determining the locations of a collection of small objects embedded in a known background medium. Based on the analysis of the induced electric dipoles in eigenstates, an algorithm is proposed to determine the test dipole that generates a pseudo-spectrum with enhanced resolution. The amplitudes in three directions of the optimal test dipole are not necessarily in phase, i.e., the optimal test dipole may not correspond to a physical direction in the real three-dimensional space. In addition, the proposed test-dipole-searching algorithm is able to deal with some special scenarios, due to the shapes and materials of objects, to which the standard MUSIC does not apply

Implementation of a Wavefront-Sensing Algorithm

Science.gov (United States)

Smith, Jeffrey S.; Dean, Bruce; Aronstein, David

2013-01-01

A computer program has been written as a unique implementation of an image-based wavefront-sensing algorithm reported in "Iterative-Transform Phase Retrieval Using Adaptive Diversity" (GSC-14879-1), NASA Tech Briefs, Vol. 31, No. 4 (April 2007), page 32. This software was originally intended for application to the James Webb Space Telescope, but is also applicable to other segmented-mirror telescopes. The software is capable of determining optical-wavefront information using, as input, a variable number of irradiance measurements collected in defocus planes about the best focal position. The software also uses input of the geometrical definition of the telescope exit pupil (otherwise denoted the pupil mask) to identify the locations of the segments of the primary telescope mirror. From the irradiance data and mask information, the software calculates an estimate of the optical wavefront (a measure of performance) of the telescope generally and across each primary mirror segment specifically. The software is capable of generating irradiance data, wavefront estimates, and basis functions for the full telescope and for each primary-mirror segment. Optionally, each of these pieces of information can be measured or computed outside of the software and incorporated during execution of the software.

Super-resolution for everybody: An image processing workflow to obtain high-resolution images with a standard confocal microscope.

Science.gov (United States)

Lam, France; Cladière, Damien; Guillaume, Cyndélia; Wassmann, Katja; Bolte, Susanne

2017-02-15

In the presented work we aimed at improving confocal imaging to obtain highest possible resolution in thick biological samples, such as the mouse oocyte. We therefore developed an image processing workflow that allows improving the lateral and axial resolution of a standard confocal microscope. Our workflow comprises refractive index matching, the optimization of microscope hardware parameters and image restoration by deconvolution. We compare two different deconvolution algorithms, evaluate the necessity of denoising and establish the optimal image restoration procedure. We validate our workflow by imaging sub resolution fluorescent beads and measuring the maximum lateral and axial resolution of the confocal system. Subsequently, we apply the parameters to the imaging and data restoration of fluorescently labelled meiotic spindles of mouse oocytes. We measure a resolution increase of approximately 2-fold in the lateral and 3-fold in the axial direction throughout a depth of 60μm. This demonstrates that with our optimized workflow we reach a resolution that is comparable to 3D-SIM-imaging, but with better depth penetration for confocal images of beads and the biological sample. Copyright © 2016 Elsevier Inc. All rights reserved.

Deconvolution algorithms applied in ultrasonics; Methodes de deconvolution en echographie ultrasonore

Energy Technology Data Exchange (ETDEWEB)

Perrot, P

1993-12-01

In a complete system of acquisition and processing of ultrasonic signals, it is often necessary at one stage to use some processing tools to get rid of the influence of the different elements of that system. By that means, the final quality of the signals in terms of resolution is improved. There are two main characteristics of ultrasonic signals which make this task difficult. Firstly, the signals generated by transducers are very often non-minimum phase. The classical deconvolution algorithms are unable to deal with such characteristics. Secondly, depending on the medium, the shape of the propagating pulse is evolving. The spatial invariance assumption often used in classical deconvolution algorithms is rarely valid. Many classical algorithms, parametric and non-parametric, have been investigated: the Wiener-type, the adaptive predictive techniques, the Oldenburg technique in the frequency domain, the minimum variance deconvolution. All the algorithms have been firstly tested on simulated data. One specific experimental set-up has also been analysed. Simulated and real data has been produced. This set-up demonstrated the interest in applying deconvolution, in terms of the achieved resolution. (author). 32 figs., 29 refs.

Algorithm of hadron energy reconstruction for combined calorimeters in the DELPHI detector

International Nuclear Information System (INIS)

Gotra, Yu.N.; Tsyganov, E.N.; Zimin, N.I.; Zinchenko, A.I.

1989-01-01

The algorithm of hadron energy reconstruction from responses of electromagnetic and hadron calorimeters is described. The investigations have been carried out using the full-scale prototype of the hadron calorimeter cylindrical part modules. The supposed algorithm allows one to improve energy resolution by 5-7% with conserving the linearly of reconstructed hadron energy. 5 refs.; 4 figs.; 1 tab

Automatic Traffic Advisory and Resolution Service (ATARS) Algorithms Including Resolution-Advisory-Register Logic. Volume 2. Sections 12 through 19. Appendices,

Science.gov (United States)

1981-06-01

resolution advisory data set; ZZITIP (all. resolution advisory data sets processed); ZIP (TRADS.IEI? 12 ST292) UI!j (VMD(TRADS.INDZI3) 9T ISEP -2) 111TRIDS.FE...PROCES featurePSBPGESP2; ZL. (NIXSEPS. NAMKSPO, SMPS, SZP20); ISEPS =0; RAISMP 0; LOOP; Get the next BADS; rYITI’ (all RIDS processed); U...THIDS.PEATBITS(l) 12 ST202) In~ (TRADS..PUJTBITS(2) X2 $TRE) J (TRADS.MTITS(3) f& STU)) :MLV I (TRIDS.SIYGLE .1 SU) THlEY ISEPS = NIQIAIS!PS.PSZP2 (TRIOS

Exploring SWOT discharge algorithm accuracy on the Sacramento River

Science.gov (United States)

Durand, M. T.; Yoon, Y.; Rodriguez, E.; Minear, J. T.; Andreadis, K.; Pavelsky, T. M.; Alsdorf, D. E.; Smith, L. C.; Bales, J. D.

2012-12-01

Scheduled for launch in 2019, the Surface Water and Ocean Topography (SWOT) satellite mission will utilize a Ka-band radar interferometer to measure river heights, widths, and slopes, globally, as well as characterize storage change in lakes and ocean surface dynamics with a spatial resolution ranging from 10 - 70 m, with temporal revisits on the order of a week. A discharge algorithm has been formulated to solve the inverse problem of characterizing river bathymetry and the roughness coefficient from SWOT observations. The algorithm uses a Bayesian Markov Chain estimation approach, treats rivers as sets of interconnected reaches (typically 5 km - 10 km in length), and produces best estimates of river bathymetry, roughness coefficient, and discharge, given SWOT observables. AirSWOT (the airborne version of SWOT) consists of a radar interferometer similar to SWOT, but mounted aboard an aircraft. AirSWOT spatial resolution will range from 1 - 35 m. In early 2013, AirSWOT will perform several flights over the Sacramento River, capturing river height, width, and slope at several different flow conditions. The Sacramento River presents an excellent target given that the river includes some stretches heavily affected by management (diversions, bypasses, etc.). AirSWOT measurements will be used to validate SWOT observation performance, but are also a unique opportunity for testing and demonstrating the capabilities and limitations of the discharge algorithm. This study uses HEC-RAS simulations of the Sacramento River to first, characterize expected discharge algorithm accuracy on the Sacramento River, and second to explore the required AirSWOT measurements needed to perform a successful inverse with the discharge algorithm. We focus on several specific research questions affecting algorithm performance: 1) To what extent do lateral inflows confound algorithm performance? We examine the ~100 km stretch of river from Colusa, CA to the Yolo Bypass, and investigate how the

Solving Hub Network Problem Using Genetic Algorithm

Directory of Open Access Journals (Sweden)

Mursyid Hasan Basri

2012-01-01

Full Text Available This paper addresses a network problem that described as follows. There are n ports that interact, and p of those will be designated as hubs. All hubs are fully interconnected. Each spoke will be allocated to only one of available hubs. Direct connection between two spokes is allowed only if they are allocated to the same hub. The latter is a distinct characteristic that differs it from pure hub-and-spoke system. In case of pure hub-and-spoke system, direct connection between two spokes is not allowed. The problem is where to locate hub ports and to which hub a spoke should be allocated so that total transportation cost is minimum. In the first model, there are some additional aspects are taken into consideration in order to achieve a better representation of the problem. The first, weekly service should be accomplished. Secondly, various vessel types should be considered. The last, a concept of inter-hub discount factor is introduced. Regarding the last aspect, it represents cost reduction factor at hub ports due to economies of scale. In practice, it is common that the cost rate for inter-hub movement is less than the cost rate for movement between hub and origin/destination. In this first model, inter-hub discount factor is assumed independent with amount of flows on inter-hub links (denoted as flow-independent discount policy. The results indicated that the patterns of enlargement of container ship size, to some degree, are similar with those in Kurokawa study. However, with regard to hub locations, the results have not represented the real practice. In the proposed model, unsatisfactory result on hub locations is addressed. One aspect that could possibly be improved to find better hub locations is inter-hub discount factor. Then inter-hub discount factor is assumed to depend on amount of inter-hub flows (denoted as flow-dependent discount policy. There are two discount functions examined in this paper. Both functions are characterized by

Multi-Objective Optimization of Hybrid Renewable Energy System Using an Enhanced Multi-Objective Evolutionary Algorithm

Directory of Open Access Journals (Sweden)

Mengjun Ming

2017-05-01

Full Text Available Due to the scarcity of conventional energy resources and the greenhouse effect, renewable energies have gained more attention. This paper proposes methods for multi-objective optimal design of hybrid renewable energy system (HRES in both isolated-island and grid-connected modes. In each mode, the optimal design aims to find suitable configurations of photovoltaic (PV panels, wind turbines, batteries and diesel generators in HRES such that the system cost and the fuel emission are minimized, and the system reliability/renewable ability (corresponding to different modes is maximized. To effectively solve this multi-objective problem (MOP, the multi-objective evolutionary algorithm based on decomposition (MOEA/D using localized penalty-based boundary intersection (LPBI method is proposed. The algorithm denoted as MOEA/D-LPBI is demonstrated to outperform its competitors on the HRES model as well as a set of benchmarks. Moreover, it effectively obtains a good approximation of Pareto optimal HRES configurations. By further considering a decision maker’s preference, the most satisfied configuration of the HRES can be identified.

High-resolution finite-difference algorithms for conservation laws

International Nuclear Information System (INIS)

Towers, J.D.

1987-01-01

A new class of Total Variation Decreasing (TVD) schemes for 2-dimensional scalar conservation laws is constructed using either flux-limited or slope-limited numerical fluxes. The schemes are proven to have formal second-order accuracy in regions where neither u/sub x/ nor y/sub y/ vanishes. A new class of high-resolution large-time-step TVD schemes is constructed by adding flux-limited correction terms to the first-order accurate large-time-step version of the Engquist-Osher scheme. The use of the transport-collapse operator in place of the exact solution operator for the construction of difference schemes is studied. The production of spurious extrema by difference schemes is studied. A simple condition guaranteeing the nonproduction of spurious extrema is derived. A sufficient class of entropy inequalities for a conservation law with a flux having a single inflection point is presented. Finite-difference schemes satisfying a discrete version of each entropy inequality are only first-order accurate

Understanding reconstructed Dante spectra using high resolution spectroscopy

Energy Technology Data Exchange (ETDEWEB)

May, M. J., E-mail: may13@llnl.gov; Widmann, K.; Kemp, G. E.; Thorn, D.; Colvin, J. D.; Schneider, M. B.; Moore, A.; Blue, B. E. [L-170 Lawrence Livermore National Laboratory, 7000 East Ave., Livermore, California 94551 (United States); Weaver, J. [Naval Research Laboratory, 4555 Overlook Ave. SW, Washington, DC 20375 (United States)

2016-11-15

The Dante is an 18 channel filtered diode array used at the National Ignition Facility (NIF) to measure the spectrally and temporally resolved radiation flux between 50 eV and 20 keV from various targets. The absolute flux is determined from the radiometric calibration of the x-ray diodes, filters, and mirrors and a reconstruction algorithm applied to the recorded voltages from each channel. The reconstructed spectra are very low resolution with features consistent with the instrument response and are not necessarily consistent with the spectral emission features from the plasma. Errors may exist between the reconstructed spectra and the actual emission features due to assumptions in the algorithm. Recently, a high resolution convex crystal spectrometer, VIRGIL, has been installed at NIF with the same line of sight as the Dante. Spectra from L-shell Ag and Xe have been recorded by both VIRGIL and Dante. Comparisons of these two spectroscopic measurements yield insights into the accuracy of the Dante reconstructions.

Time reversal and phase coherent music techniques for super-resolution ultrasound imaging

Science.gov (United States)

Huang, Lianjie; Labyed, Yassin

2018-05-01

Systems and methods for super-resolution ultrasound imaging using a windowed and generalized TR-MUSIC algorithm that divides the imaging region into overlapping sub-regions and applies the TR-MUSIC algorithm to the windowed backscattered ultrasound signals corresponding to each sub-region. The algorithm is also structured to account for the ultrasound attenuation in the medium and the finite-size effects of ultrasound transducer elements. A modified TR-MUSIC imaging algorithm is used to account for ultrasound scattering from both density and compressibility contrasts. The phase response of ultrasound transducer elements is accounted for in a PC-MUSIC system.

Fast weighted centroid algorithm for single particle localization near the information limit.

Science.gov (United States)

Fish, Jeremie; Scrimgeour, Jan

2015-07-10

A simple weighting scheme that enhances the localization precision of center of mass calculations for radially symmetric intensity distributions is presented. The algorithm effectively removes the biasing that is common in such center of mass calculations. Localization precision compares favorably with other localization algorithms used in super-resolution microscopy and particle tracking, while significantly reducing the processing time and memory usage. We expect that the algorithm presented will be of significant utility when fast computationally lightweight particle localization or tracking is desired.

A high accuracy algorithm of displacement measurement for a micro-positioning stage

Directory of Open Access Journals (Sweden)

Xiang Zhang

2017-05-01

Full Text Available A high accuracy displacement measurement algorithm for a two degrees of freedom compliant precision micro-positioning stage is proposed based on the computer micro-vision technique. The algorithm consists of an integer-pixel and a subpixel matching procedure. Series of simulations are conducted to verify the proposed method. The results show that the proposed algorithm possesses the advantages of high precision and stability, the resolution can attain to 0.01 pixel theoretically. In addition, the consuming time is reduced about 6.7 times compared with the classical normalized cross correlation algorithm. To validate the practical performance of the proposed algorithm, a laser interferometer measurement system (LIMS is built up. The experimental results demonstrate that the algorithm has better adaptability than that of the LIMS.

WE-AB-209-06: Dynamic Collimator Trajectory Algorithm for Use in VMAT Treatment Deliveries

Energy Technology Data Exchange (ETDEWEB)

MacDonald, L [Department of Medical Physics, Dalhousie University, Halifax, Nova Scotia, CA (Canada); Thomas, C; Syme, A [Department of Medical Physics, Dalhousie University, Halifax, Nova Scotia, CA (Canada); Department of Radiation Oncology, Dalhousie University, Halifax, Nova Scotia (Canada); Medical Physics, Nova Scotia Cancer Centre, Halifax, Nova Scotia (Canada)

2016-06-15

Purpose: To develop advanced dynamic collimator positioning algorithms for optimal beam’s-eye-view (BEV) fitting of targets in VMAT procedures, including multiple metastases stereotactic radiosurgery procedures. Methods: A trajectory algorithm was developed, which can dynamically modify the angle of the collimator as a function of VMAT control point to provide optimized collimation of target volume(s). Central to this algorithm is a concept denoted “whitespace”, defined as area within the jaw-defined BEV field, outside of the PTV, and not shielded by the MLC when fit to the PTV. Calculating whitespace at all collimator angles and every control point, a two-dimensional topographical map depicting the tightness-of-fit of the MLC was generated. A variety of novel searching algorithms identified a number of candidate trajectories of continuous collimator motion. Ranking these candidate trajectories according to their accrued whitespace value produced an optimal solution for navigation of this map. Results: All trajectories were normalized to minimum possible (i.e. calculated without consideration of collimator motion constraints) accrued whitespace. On an acoustic neuroma case, a random walk algorithm generated a trajectory with 151% whitespace; random walk including a mandatory anchor point improved this to 148%; gradient search produced a trajectory with 137%; and bi-directional gradient search generated a trajectory with 130% whitespace. For comparison, a fixed collimator angle of 30° and 330° accumulated 272% and 228% of whitespace, respectively. The algorithm was tested on a clinical case with two metastases (single isocentre) and identified collimator angles that allow for simultaneous irradiation of the PTVs while minimizing normal tissue irradiation. Conclusion: Dynamic collimator trajectories have the potential to improve VMAT deliveries through increased efficiency and reduced normal tissue dose, especially in treatment of multiple cranial metastases

WE-AB-209-06: Dynamic Collimator Trajectory Algorithm for Use in VMAT Treatment Deliveries

International Nuclear Information System (INIS)

MacDonald, L; Thomas, C; Syme, A

2016-01-01

Purpose: To develop advanced dynamic collimator positioning algorithms for optimal beam’s-eye-view (BEV) fitting of targets in VMAT procedures, including multiple metastases stereotactic radiosurgery procedures. Methods: A trajectory algorithm was developed, which can dynamically modify the angle of the collimator as a function of VMAT control point to provide optimized collimation of target volume(s). Central to this algorithm is a concept denoted “whitespace”, defined as area within the jaw-defined BEV field, outside of the PTV, and not shielded by the MLC when fit to the PTV. Calculating whitespace at all collimator angles and every control point, a two-dimensional topographical map depicting the tightness-of-fit of the MLC was generated. A variety of novel searching algorithms identified a number of candidate trajectories of continuous collimator motion. Ranking these candidate trajectories according to their accrued whitespace value produced an optimal solution for navigation of this map. Results: All trajectories were normalized to minimum possible (i.e. calculated without consideration of collimator motion constraints) accrued whitespace. On an acoustic neuroma case, a random walk algorithm generated a trajectory with 151% whitespace; random walk including a mandatory anchor point improved this to 148%; gradient search produced a trajectory with 137%; and bi-directional gradient search generated a trajectory with 130% whitespace. For comparison, a fixed collimator angle of 30° and 330° accumulated 272% and 228% of whitespace, respectively. The algorithm was tested on a clinical case with two metastases (single isocentre) and identified collimator angles that allow for simultaneous irradiation of the PTVs while minimizing normal tissue irradiation. Conclusion: Dynamic collimator trajectories have the potential to improve VMAT deliveries through increased efficiency and reduced normal tissue dose, especially in treatment of multiple cranial metastases

Mobile Robots Path Planning Using the Overall Conflict Resolution and Time Baseline Coordination

Directory of Open Access Journals (Sweden)

Yong Ma

2014-01-01

Full Text Available This paper aims at resolving the path planning problem in a time-varying environment based on the idea of overall conflict resolution and the algorithm of time baseline coordination. The basic task of the introduced path planning algorithms is to fulfill the automatic generation of the shortest paths from the defined start poses to their end poses with consideration of generous constraints for multiple mobile robots. Building on this, by using the overall conflict resolution, within the polynomial based paths, we take into account all the constraints including smoothness, motion boundary, kinematics constraints, obstacle avoidance, and safety constraints among robots together. And time baseline coordination algorithm is proposed to process the above formulated problem. The foremost strong point is that much time can be saved with our approach. Numerical simulations verify the effectiveness of our approach.

Improvement of resolution in full-view linear-array photoacoustic computed tomography using a novel adaptive weighting method

Science.gov (United States)

Omidi, Parsa; Diop, Mamadou; Carson, Jeffrey; Nasiriavanaki, Mohammadreza

2017-03-01

Linear-array-based photoacoustic computed tomography is a popular methodology for deep and high resolution imaging. However, issues such as phase aberration, side-lobe effects, and propagation limitations deteriorate the resolution. The effect of phase aberration due to acoustic attenuation and constant assumption of the speed of sound (SoS) can be reduced by applying an adaptive weighting method such as the coherence factor (CF). Utilizing an adaptive beamforming algorithm such as the minimum variance (MV) can improve the resolution at the focal point by eliminating the side-lobes. Moreover, invisibility of directional objects emitting parallel to the detection plane, such as vessels and other absorbing structures stretched in the direction perpendicular to the detection plane can degrade resolution. In this study, we propose a full-view array level weighting algorithm in which different weighs are assigned to different positions of the linear array based on an orientation algorithm which uses the histogram of oriented gradient (HOG). Simulation results obtained from a synthetic phantom show the superior performance of the proposed method over the existing reconstruction methods.

Scale-Aware Pansharpening Algorithm for Agricultural Fragmented Landscapes

Directory of Open Access Journals (Sweden)

Mario Lillo-Saavedra

2016-10-01

Full Text Available Remote sensing (RS has played an important role in extensive agricultural monitoring and management for several decades. However, the current spatial resolution of satellite imagery does not have enough definition to generalize its use in highly-fragmented agricultural landscapes, which represents a significant percentage of the world’s total cultivated surface. To characterize and analyze this type of landscape, multispectral (MS images with high and very high spatial resolutions are required. Multi-source image fusion algorithms are normally used to improve the spatial resolution of images with a medium spatial resolution. In particular, pansharpening (PS methods allow one to produce high-resolution MS images through a coherent integration of spatial details from a panchromatic (PAN image with spectral information from an MS. The spectral and spatial quality of source images must be preserved to be useful in RS tasks. Different PS strategies provide different trade-offs between the spectral and the spatial quality of the fused images. Considering that agricultural landscape images contain many levels of significant structures and edges, the PS algorithms based on filtering processes must be scale-aware and able to remove different levels of detail in any input images. In this work, a new PS methodology based on a rolling guidance filter (RGF is proposed. The main contribution of this new methodology is to produce artifact-free pansharpened images, improving the MS edges with a scale-aware approach. Three images have been used, and more than 150 experiments were carried out. An objective comparison with widely-used methodologies shows the capability of the proposed method as a powerful tool to obtain pansharpened images preserving the spatial and spectral information.

Hybrid Optimization of Object-Based Classification in High-Resolution Images Using Continous ANT Colony Algorithm with Emphasis on Building Detection

Science.gov (United States)

Tamimi, E.; Ebadi, H.; Kiani, A.

2017-09-01

Automatic building detection from High Spatial Resolution (HSR) images is one of the most important issues in Remote Sensing (RS). Due to the limited number of spectral bands in HSR images, using other features will lead to improve accuracy. By adding these features, the presence probability of dependent features will be increased, which leads to accuracy reduction. In addition, some parameters should be determined in Support Vector Machine (SVM) classification. Therefore, it is necessary to simultaneously determine classification parameters and select independent features according to image type. Optimization algorithm is an efficient method to solve this problem. On the other hand, pixel-based classification faces several challenges such as producing salt-paper results and high computational time in high dimensional data. Hence, in this paper, a novel method is proposed to optimize object-based SVM classification by applying continuous Ant Colony Optimization (ACO) algorithm. The advantages of the proposed method are relatively high automation level, independency of image scene and type, post processing reduction for building edge reconstruction and accuracy improvement. The proposed method was evaluated by pixel-based SVM and Random Forest (RF) classification in terms of accuracy. In comparison with optimized pixel-based SVM classification, the results showed that the proposed method improved quality factor and overall accuracy by 17% and 10%, respectively. Also, in the proposed method, Kappa coefficient was improved by 6% rather than RF classification. Time processing of the proposed method was relatively low because of unit of image analysis (image object). These showed the superiority of the proposed method in terms of time and accuracy.

A multi-sensor data-driven methodology for all-sky passive microwave inundation retrieval

Science.gov (United States)

Takbiri, Zeinab; Ebtehaj, Ardeshir M.; Foufoula-Georgiou, Efi

2017-06-01

We present a multi-sensor Bayesian passive microwave retrieval algorithm for flood inundation mapping at high spatial and temporal resolutions. The algorithm takes advantage of observations from multiple sensors in optical, short-infrared, and microwave bands, thereby allowing for detection and mapping of the sub-pixel fraction of inundated areas under almost all-sky conditions. The method relies on a nearest-neighbor search and a modern sparsity-promoting inversion method that make use of an a priori dataset in the form of two joint dictionaries. These dictionaries contain almost overlapping observations by the Special Sensor Microwave Imager and Sounder (SSMIS) on board the Defense Meteorological Satellite Program (DMSP) F17 satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Aqua and Terra satellites. Evaluation of the retrieval algorithm over the Mekong Delta shows that it is capable of capturing to a good degree the inundation diurnal variability due to localized convective precipitation. At longer timescales, the results demonstrate consistency with the ground-based water level observations, denoting that the method is properly capturing inundation seasonal patterns in response to regional monsoonal rain. The calculated Euclidean distance, rank-correlation, and also copula quantile analysis demonstrate a good agreement between the outputs of the algorithm and the observed water levels at monthly and daily timescales. The current inundation products are at a resolution of 12.5 km and taken twice per day, but a higher resolution (order of 5 km and every 3 h) can be achieved using the same algorithm with the dictionary populated by the Global Precipitation Mission (GPM) Microwave Imager (GMI) products.

A multi-sensor data-driven methodology for all-sky passive microwave inundation retrieval

Directory of Open Access Journals (Sweden)

Z. Takbiri

2017-06-01

Full Text Available We present a multi-sensor Bayesian passive microwave retrieval algorithm for flood inundation mapping at high spatial and temporal resolutions. The algorithm takes advantage of observations from multiple sensors in optical, short-infrared, and microwave bands, thereby allowing for detection and mapping of the sub-pixel fraction of inundated areas under almost all-sky conditions. The method relies on a nearest-neighbor search and a modern sparsity-promoting inversion method that make use of an a priori dataset in the form of two joint dictionaries. These dictionaries contain almost overlapping observations by the Special Sensor Microwave Imager and Sounder (SSMIS on board the Defense Meteorological Satellite Program (DMSP F17 satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS on board the Aqua and Terra satellites. Evaluation of the retrieval algorithm over the Mekong Delta shows that it is capable of capturing to a good degree the inundation diurnal variability due to localized convective precipitation. At longer timescales, the results demonstrate consistency with the ground-based water level observations, denoting that the method is properly capturing inundation seasonal patterns in response to regional monsoonal rain. The calculated Euclidean distance, rank-correlation, and also copula quantile analysis demonstrate a good agreement between the outputs of the algorithm and the observed water levels at monthly and daily timescales. The current inundation products are at a resolution of 12.5 km and taken twice per day, but a higher resolution (order of 5 km and every 3 h can be achieved using the same algorithm with the dictionary populated by the Global Precipitation Mission (GPM Microwave Imager (GMI products.

Overcoming Registration Uncertainty in Image Super-Resolution: Maximize or Marginalize?

Directory of Open Access Journals (Sweden)

Andrew Zisserman

2007-01-01

Full Text Available In multiple-image super-resolution, a high-resolution image is estimated from a number of lower-resolution images. This usually involves computing the parameters of a generative imaging model (such as geometric and photometric registration, and blur and obtaining a MAP estimate by minimizing a cost function including an appropriate prior. Two alternative approaches are examined. First, both registrations and the super-resolution image are found simultaneously using a joint MAP optimization. Second, we perform Bayesian integration over the unknown image registration parameters, deriving a cost function whose only variables of interest are the pixel values of the super-resolution image. We also introduce a scheme to learn the parameters of the image prior as part of the super-resolution algorithm. We show examples on a number of real sequences including multiple stills, digital video, and DVDs of movies.

A New Algorithm for Cartographic Simplification of Streams and Lakes Using Deviation Angles and Error Bands

Directory of Open Access Journals (Sweden)

Türkay Gökgöz

2015-10-01

Full Text Available Multi-representation databases (MRDBs are used in several geographical information system applications for different purposes. MRDBs are mainly obtained through model and cartographic generalizations. Simplification is the essential operator of cartographic generalization, and streams and lakes are essential features in hydrography. In this study, a new algorithm was developed for the simplification of streams and lakes. In this algorithm, deviation angles and error bands are used to determine the characteristic vertices and the planimetric accuracy of the features, respectively. The algorithm was tested using a high-resolution national hydrography dataset of Pomme de Terre, a sub-basin in the USA. To assess the performance of the new algorithm, the Bend Simplify and Douglas-Peucker algorithms, the medium-resolution hydrography dataset of the sub-basin, and Töpfer’s radical law were used. For quantitative analysis, the vertex numbers, the lengths, and the sinuosity values were computed. Consequently, it was shown that the new algorithm was able to meet the main requirements (i.e., accuracy, legibility and aesthetics, and storage.

Single-Image Super-Resolution Based on Rational Fractal Interpolation.

Science.gov (United States)

Zhang, Yunfeng; Fan, Qinglan; Bao, Fangxun; Liu, Yifang; Zhang, Caiming

2018-08-01

This paper presents a novel single-image super-resolution (SR) procedure, which upscales a given low-resolution (LR) input image to a high-resolution image while preserving the textural and structural information. First, we construct a new type of bivariate rational fractal interpolation model and investigate its analytical properties. This model has different forms of expression with various values of the scaling factors and shape parameters; thus, it can be employed to better describe image features than current interpolation schemes. Furthermore, this model combines the advantages of rational interpolation and fractal interpolation, and its effectiveness is validated through theoretical analysis. Second, we develop a single-image SR algorithm based on the proposed model. The LR input image is divided into texture and non-texture regions, and then, the image is interpolated according to the characteristics of the local structure. Specifically, in the texture region, the scaling factor calculation is the critical step. We present a method to accurately calculate scaling factors based on local fractal analysis. Extensive experiments and comparisons with the other state-of-the-art methods show that our algorithm achieves competitive performance, with finer details and sharper edges.

Solutions on high-resolution multiple configuration system sensors

Science.gov (United States)

Liu, Hua; Ding, Quanxin; Guo, Chunjie; Zhou, Liwei

2014-11-01

For aim to achieve an improved resolution in modern image domain, a method of continuous zoom multiple configuration, with a core optics is attempt to establish model by novel principle on energy transfer and high accuracy localization, by which the system resolution can be improved with a level in nano meters. A comparative study on traditional vs modern methods can demonstrate that the dialectical relationship and their balance is important, among Merit function, Optimization algorithms and Model parameterization. The effect of system evaluated criterion that MTF, REA, RMS etc. can support our arguments qualitatively.

Structure-Based Algorithms for Microvessel Classification

KAUST Repository

Smith, Amy F.

2015-02-01

© 2014 The Authors. Microcirculation published by John Wiley & Sons Ltd. Objective: Recent developments in high-resolution imaging techniques have enabled digital reconstruction of three-dimensional sections of microvascular networks down to the capillary scale. To better interpret these large data sets, our goal is to distinguish branching trees of arterioles and venules from capillaries. Methods: Two novel algorithms are presented for classifying vessels in microvascular anatomical data sets without requiring flow information. The algorithms are compared with a classification based on observed flow directions (considered the gold standard), and with an existing resistance-based method that relies only on structural data. Results: The first algorithm, developed for networks with one arteriolar and one venular tree, performs well in identifying arterioles and venules and is robust to parameter changes, but incorrectly labels a significant number of capillaries as arterioles or venules. The second algorithm, developed for networks with multiple inlets and outlets, correctly identifies more arterioles and venules, but is more sensitive to parameter changes. Conclusions: The algorithms presented here can be used to classify microvessels in large microvascular data sets lacking flow information. This provides a basis for analyzing the distinct geometrical properties and modelling the functional behavior of arterioles, capillaries, and venules.

Accuracy assessment of tree crown detection using local maxima and multi-resolution segmentation

International Nuclear Information System (INIS)

Khalid, N; Hamid, J R A; Latif, Z A

2014-01-01

Diversity of trees forms an important component in the forest ecosystems and needs proper inventories to assist the forest personnel in their daily activities. However, tree parameter measurements are often constrained by physical inaccessibility to site locations, high costs, and time. With the advancement in remote sensing technology, such as the provision of higher spatial and spectral resolution of imagery, a number of developed algorithms fulfil the needs of accurate tree inventories information in a cost effective and timely manner over larger forest areas. This study intends to generate tree distribution map in Ampang Forest Reserve using the Local Maxima and Multi-Resolution image segmentation algorithm. The utilization of recent worldview-2 imagery with Local Maxima and Multi-Resolution image segmentation proves to be capable of detecting and delineating the tree crown in its accurate standing position

Isotope specific resolution recovery image reconstruction in high resolution PET imaging

Energy Technology Data Exchange (ETDEWEB)

Kotasidis, Fotis A. [Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211 Geneva, Switzerland and Wolfson Molecular Imaging Centre, MAHSC, University of Manchester, M20 3LJ, Manchester (United Kingdom); Angelis, Georgios I. [Faculty of Health Sciences, Brain and Mind Research Institute, University of Sydney, NSW 2006, Sydney (Australia); Anton-Rodriguez, Jose; Matthews, Julian C. [Wolfson Molecular Imaging Centre, MAHSC, University of Manchester, Manchester M20 3LJ (United Kingdom); Reader, Andrew J. [Montreal Neurological Institute, McGill University, Montreal QC H3A 2B4, Canada and Department of Biomedical Engineering, Division of Imaging Sciences and Biomedical Engineering, King' s College London, St. Thomas’ Hospital, London SE1 7EH (United Kingdom); Zaidi, Habib [Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211 Geneva (Switzerland); Geneva Neuroscience Centre, Geneva University, CH-1205 Geneva (Switzerland); Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, PO Box 30 001, Groningen 9700 RB (Netherlands)

2014-05-15

Purpose: Measuring and incorporating a scanner-specific point spread function (PSF) within image reconstruction has been shown to improve spatial resolution in PET. However, due to the short half-life of clinically used isotopes, other long-lived isotopes not used in clinical practice are used to perform the PSF measurements. As such, non-optimal PSF models that do not correspond to those needed for the data to be reconstructed are used within resolution modeling (RM) image reconstruction, usually underestimating the true PSF owing to the difference in positron range. In high resolution brain and preclinical imaging, this effect is of particular importance since the PSFs become more positron range limited and isotope-specific PSFs can help maximize the performance benefit from using resolution recovery image reconstruction algorithms. Methods: In this work, the authors used a printing technique to simultaneously measure multiple point sources on the High Resolution Research Tomograph (HRRT), and the authors demonstrated the feasibility of deriving isotope-dependent system matrices from fluorine-18 and carbon-11 point sources. Furthermore, the authors evaluated the impact of incorporating them within RM image reconstruction, using carbon-11 phantom and clinical datasets on the HRRT. Results: The results obtained using these two isotopes illustrate that even small differences in positron range can result in different PSF maps, leading to further improvements in contrast recovery when used in image reconstruction. The difference is more pronounced in the centre of the field-of-view where the full width at half maximum (FWHM) from the positron range has a larger contribution to the overall FWHM compared to the edge where the parallax error dominates the overall FWHM. Conclusions: Based on the proposed methodology, measured isotope-specific and spatially variant PSFs can be reliably derived and used for improved spatial resolution and variance performance in resolution

Isotope specific resolution recovery image reconstruction in high resolution PET imaging

International Nuclear Information System (INIS)

Kotasidis, Fotis A.; Angelis, Georgios I.; Anton-Rodriguez, Jose; Matthews, Julian C.; Reader, Andrew J.; Zaidi, Habib

2014-01-01

Purpose: Measuring and incorporating a scanner-specific point spread function (PSF) within image reconstruction has been shown to improve spatial resolution in PET. However, due to the short half-life of clinically used isotopes, other long-lived isotopes not used in clinical practice are used to perform the PSF measurements. As such, non-optimal PSF models that do not correspond to those needed for the data to be reconstructed are used within resolution modeling (RM) image reconstruction, usually underestimating the true PSF owing to the difference in positron range. In high resolution brain and preclinical imaging, this effect is of particular importance since the PSFs become more positron range limited and isotope-specific PSFs can help maximize the performance benefit from using resolution recovery image reconstruction algorithms. Methods: In this work, the authors used a printing technique to simultaneously measure multiple point sources on the High Resolution Research Tomograph (HRRT), and the authors demonstrated the feasibility of deriving isotope-dependent system matrices from fluorine-18 and carbon-11 point sources. Furthermore, the authors evaluated the impact of incorporating them within RM image reconstruction, using carbon-11 phantom and clinical datasets on the HRRT. Results: The results obtained using these two isotopes illustrate that even small differences in positron range can result in different PSF maps, leading to further improvements in contrast recovery when used in image reconstruction. The difference is more pronounced in the centre of the field-of-view where the full width at half maximum (FWHM) from the positron range has a larger contribution to the overall FWHM compared to the edge where the parallax error dominates the overall FWHM. Conclusions: Based on the proposed methodology, measured isotope-specific and spatially variant PSFs can be reliably derived and used for improved spatial resolution and variance performance in resolution

Isotope specific resolution recovery image reconstruction in high resolution PET imaging.

Science.gov (United States)

Kotasidis, Fotis A; Angelis, Georgios I; Anton-Rodriguez, Jose; Matthews, Julian C; Reader, Andrew J; Zaidi, Habib

2014-05-01

Measuring and incorporating a scanner-specific point spread function (PSF) within image reconstruction has been shown to improve spatial resolution in PET. However, due to the short half-life of clinically used isotopes, other long-lived isotopes not used in clinical practice are used to perform the PSF measurements. As such, non-optimal PSF models that do not correspond to those needed for the data to be reconstructed are used within resolution modeling (RM) image reconstruction, usually underestimating the true PSF owing to the difference in positron range. In high resolution brain and preclinical imaging, this effect is of particular importance since the PSFs become more positron range limited and isotope-specific PSFs can help maximize the performance benefit from using resolution recovery image reconstruction algorithms. In this work, the authors used a printing technique to simultaneously measure multiple point sources on the High Resolution Research Tomograph (HRRT), and the authors demonstrated the feasibility of deriving isotope-dependent system matrices from fluorine-18 and carbon-11 point sources. Furthermore, the authors evaluated the impact of incorporating them within RM image reconstruction, using carbon-11 phantom and clinical datasets on the HRRT. The results obtained using these two isotopes illustrate that even small differences in positron range can result in different PSF maps, leading to further improvements in contrast recovery when used in image reconstruction. The difference is more pronounced in the centre of the field-of-view where the full width at half maximum (FWHM) from the positron range has a larger contribution to the overall FWHM compared to the edge where the parallax error dominates the overall FWHM. Based on the proposed methodology, measured isotope-specific and spatially variant PSFs can be reliably derived and used for improved spatial resolution and variance performance in resolution recovery image reconstruction. The

A multiresolution remeshed Vortex-In-Cell algorithm using patches

DEFF Research Database (Denmark)

Rasmussen, Johannes Tophøj; Cottet, Georges-Henri; Walther, Jens Honore

2011-01-01

We present a novel multiresolution Vortex-In-Cell algorithm using patches of varying resolution. The Poisson equation relating the fluid vorticity and velocity is solved using Fast Fourier Transforms subject to free space boundary conditions. Solid boundaries are implemented using the semi...

Highlights of TOMS Version 9 Total Ozone Algorithm

Science.gov (United States)

Bhartia, Pawan; Haffner, David

2012-01-01

The fundamental basis of TOMS total ozone algorithm was developed some 45 years ago by Dave and Mateer. It was designed to estimate total ozone from satellite measurements of the backscattered UV radiances at few discrete wavelengths in the Huggins ozone absorption band (310-340 nm). Over the years, as the need for higher accuracy in measuring total ozone from space has increased, several improvements to the basic algorithms have been made. They include: better correction for the effects of aerosols and clouds, an improved method to account for the variation in shape of ozone profiles with season, latitude, and total ozone, and a multi-wavelength correction for remaining profile shape errors. These improvements have made it possible to retrieve total ozone with just 3 spectral channels of moderate spectral resolution (approx. 1 nm) with accuracy comparable to state-of-the-art spectral fitting algorithms like DOAS that require high spectral resolution measurements at large number of wavelengths. One of the deficiencies of the TOMS algorithm has been that it doesn't provide an error estimate. This is a particular problem in high latitudes when the profile shape errors become significant and vary with latitude, season, total ozone, and instrument viewing geometry. The primary objective of the TOMS V9 algorithm is to account for these effects in estimating the error bars. This is done by a straightforward implementation of the Rodgers optimum estimation method using a priori ozone profiles and their error covariances matrices constructed using Aura MLS and ozonesonde data. The algorithm produces a vertical ozone profile that contains 1-2.5 pieces of information (degrees of freedom of signal) depending upon solar zenith angle (SZA). The profile is integrated to obtain the total column. We provide information that shows the altitude range in which the profile is best determined by the measurements. One can use this information in data assimilation and analysis. A side

Almagest, a new trackless ring finding algorithm

Energy Technology Data Exchange (ETDEWEB)

Lamanna, G., E-mail: gianluca.lamanna@cern.ch

2014-12-01

A fast ring finding algorithm is a crucial point to allow the use of RICH in on-line trigger selection. The present algorithms are either too slow (with respect to the incoming data rate) or need the information coming from a tracking system. Digital image techniques, assuming limited computing power (as for example Hough transform), are not perfectly robust for what concerns the noise immunity. We present a novel technique based on Ptolemy's theorem for multi-ring pattern recognition. Starting from purely geometrical considerations, this algorithm (also known as “Almagest”) allows fast and trackless rings reconstruction, with spatial resolution comparable with other offline techniques. Almagest is particularly suitable for parallel implementation on multi-cores machines. Preliminary tests on GPUs (multi-cores video card processors) show that, thanks to an execution time smaller than 10 μs per event, this algorithm could be employed for on-line selection in trigger systems. The user case of the NA62 RICH trigger, based on GPU, will be discussed. - Highlights: • A new algorithm for fast multiple ring searching in RICH detectors is presented. • The Almagest algorithm exploits the computing power of Graphics processers (GPUs). • A preliminary implementation for on-line triggering in the NA62 experiment shows encouraging results.

Averaging scheme for atomic resolution off-axis electron holograms.

Science.gov (United States)

Niermann, T; Lehmann, M

2014-08-01

All micrographs are limited by shot-noise, which is intrinsic to the detection process of electrons. For beam insensitive specimen this limitation can in principle easily be circumvented by prolonged exposure times. However, in the high-resolution regime several instrumental instabilities limit the applicable exposure time. Particularly in the case of off-axis holography the holograms are highly sensitive to the position and voltage of the electron-optical biprism. We present a novel reconstruction algorithm to average series of off-axis holograms while compensating for specimen drift, biprism drift, drift of biprism voltage, and drift of defocus, which all might cause problematic changes from exposure to exposure. We show an application of the algorithm utilizing also the possibilities of double biprism holography, which results in a high quality exit-wave reconstruction with 75 pm resolution at a very high signal-to-noise ratio. Copyright © 2014 Elsevier Ltd. All rights reserved.

Improved algorithm for computerized detection and quantification of pulmonary emphysema at high-resolution computed tomography (HRCT)

Science.gov (United States)

Tylen, Ulf; Friman, Ola; Borga, Magnus; Angelhed, Jan-Erik

2001-05-01

Emphysema is characterized by destruction of lung tissue with development of small or large holes within the lung. These areas will have Hounsfield values (HU) approaching -1000. It is possible to detect and quantificate such areas using simple density mask technique. The edge enhancement reconstruction algorithm, gravity and motion of the heart and vessels during scanning causes artefacts, however. The purpose of our work was to construct an algorithm that detects such image artefacts and corrects them. The first step is to apply inverse filtering to the image removing much of the effect of the edge enhancement reconstruction algorithm. The next step implies computation of the antero-posterior density gradient caused by gravity and correction for that. Motion artefacts are in a third step corrected for by use of normalized averaging, thresholding and region growing. Twenty healthy volunteers were investigated, 10 with slight emphysema and 10 without. Using simple density mask technique it was not possible to separate persons with disease from those without. Our algorithm improved separation of the two groups considerably. Our algorithm needs further refinement, but may form a basis for further development of methods for computerized diagnosis and quantification of emphysema by HRCT.

SU-G-JeP1-12: Head-To-Head Performance Characterization of Two Multileaf Collimator Tracking Algorithms for Radiotherapy

International Nuclear Information System (INIS)

Caillet, V; Colvill, E; O’Brien, R; Keall, P; Poulsen, P; Moore, D; Booth, J; Sawant, A

2016-01-01

Purpose: Multi-leaf collimator (MLC) tracking is being clinically pioneered to continuously compensate for thoracic and abdominal motion during radiotherapy. The purpose of this work is to characterize the performance of two MLC tracking algorithms for cancer radiotherapy, based on a direct optimization and a piecewise leaf fitting approach respectively. Methods: To test the algorithms, both physical and in silico experiments were performed. Previously published high and low modulation VMAT plans for lung and prostate cancer cases were used along with eight patient-measured organ-specific trajectories. For both MLC tracking algorithm, the plans were run with their corresponding patient trajectories. The physical experiments were performed on a Trilogy Varian linac and a programmable phantom (HexaMotion platform). For each MLC tracking algorithm, plan and patient trajectory, the tracking accuracy was quantified as the difference in aperture area between ideal and fitted MLC. To compare algorithms, the average cumulative tracking error area for each experiment was calculated. The two-sample Kolmogorov-Smirnov (KS) test was used to evaluate the cumulative tracking errors between algorithms. Results: Comparison of tracking errors for the physical and in silico experiments showed minor differences between the two algorithms. The KS D-statistics for the physical experiments were below 0.05 denoting no significant differences between the two distributions pattern and the average error area (direct optimization/piecewise leaf-fitting) were comparable (66.64 cm2/65.65 cm2). For the in silico experiments, the KS D-statistics were below 0.05 and the average errors area were also equivalent (49.38 cm2/48.98 cm2). Conclusion: The comparison between the two leaf fittings algorithms demonstrated no significant differences in tracking errors, neither in a clinically realistic environment nor in silico. The similarities in the two independent algorithms give confidence in the use

SU-G-JeP1-12: Head-To-Head Performance Characterization of Two Multileaf Collimator Tracking Algorithms for Radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Caillet, V; Colvill, E [School of Medecine, The University of Sydney, Sydney, NSW (Australia); Royal North Shore Hospital, St Leonards, Sydney (Australia); O’Brien, R; Keall, P [School of Medecine, The University of Sydney, Sydney, NSW (Australia); Poulsen, P [Aarhus University Hospital, Aarhus (Denmark); Moore, D [UT Southwestern Medical Center, Dallas, TX (United States); University of Maryland School of Medicine, Baltimore, MD (United States); Booth, J [Royal North Shore Hospital, St Leonards, Sydney (Australia); Sawant, A [University of Maryland School of Medicine, Baltimore, MD (United States)

2016-06-15

Purpose: Multi-leaf collimator (MLC) tracking is being clinically pioneered to continuously compensate for thoracic and abdominal motion during radiotherapy. The purpose of this work is to characterize the performance of two MLC tracking algorithms for cancer radiotherapy, based on a direct optimization and a piecewise leaf fitting approach respectively. Methods: To test the algorithms, both physical and in silico experiments were performed. Previously published high and low modulation VMAT plans for lung and prostate cancer cases were used along with eight patient-measured organ-specific trajectories. For both MLC tracking algorithm, the plans were run with their corresponding patient trajectories. The physical experiments were performed on a Trilogy Varian linac and a programmable phantom (HexaMotion platform). For each MLC tracking algorithm, plan and patient trajectory, the tracking accuracy was quantified as the difference in aperture area between ideal and fitted MLC. To compare algorithms, the average cumulative tracking error area for each experiment was calculated. The two-sample Kolmogorov-Smirnov (KS) test was used to evaluate the cumulative tracking errors between algorithms. Results: Comparison of tracking errors for the physical and in silico experiments showed minor differences between the two algorithms. The KS D-statistics for the physical experiments were below 0.05 denoting no significant differences between the two distributions pattern and the average error area (direct optimization/piecewise leaf-fitting) were comparable (66.64 cm2/65.65 cm2). For the in silico experiments, the KS D-statistics were below 0.05 and the average errors area were also equivalent (49.38 cm2/48.98 cm2). Conclusion: The comparison between the two leaf fittings algorithms demonstrated no significant differences in tracking errors, neither in a clinically realistic environment nor in silico. The similarities in the two independent algorithms give confidence in the use

Statistical Assessment of Gene Fusion Detection Algorithms using RNASequencing Data

NARCIS (Netherlands)

Varadan, V.; Janevski, A.; Kamalakaran, S.; Banerjee, N.; Harris, L.; Dimitrova, D.

2012-01-01

The detection and quantification of fusion transcripts has both biological and clinical implications. RNA sequencing technology provides a means for unbiased and high resolution characterization of fusion transcript information in tissue samples. We evaluated two fusiondetection algorithms,

Empirical algorithms to estimate water column pH in the Southern Ocean

Science.gov (United States)

Williams, N. L.; Juranek, L. W.; Johnson, K. S.; Feely, R. A.; Riser, S. C.; Talley, L. D.; Russell, J. L.; Sarmiento, J. L.; Wanninkhof, R.

2016-04-01

Empirical algorithms are developed using high-quality GO-SHIP hydrographic measurements of commonly measured parameters (temperature, salinity, pressure, nitrate, and oxygen) that estimate pH in the Pacific sector of the Southern Ocean. The coefficients of determination, R2, are 0.98 for pH from nitrate (pHN) and 0.97 for pH from oxygen (pHOx) with RMS errors of 0.010 and 0.008, respectively. These algorithms are applied to Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) biogeochemical profiling floats, which include novel sensors (pH, nitrate, oxygen, fluorescence, and backscatter). These algorithms are used to estimate pH on floats with no pH sensors and to validate and adjust pH sensor data from floats with pH sensors. The adjusted float data provide, for the first time, seasonal cycles in surface pH on weekly resolution that range from 0.05 to 0.08 on weekly resolution for the Pacific sector of the Southern Ocean.

Ensemble variational Bayes tensor factorization for super resolution of CFRP debond detection

Science.gov (United States)

Lu, Peng; Gao, Bin; Feng, Qizhi; Yang, Yang; Woo, W. L.; Tian, Gui Yun

2017-09-01

The carbon fiber reinforced polymer (CFRP) is widely used in aircraft and wind turbine blades. The common type of CFRP defect is debond. Optical pulse thermographic nondestructive evaluation (OPTNDE) and relevant thermal feature extraction algorithms are generally used to detect the debond. However, the resolution of detection performance remain as challenges. In this paper, the ensemble variational Bayes tensor factorization has been proposed to conduct super resolution of the debond detection. The algorithm is based on the framework of variational Bayes tensor factorization and it constructs spatial-transient multi-layer mining structure which can significantly enhance the contrast ratio between the defective regions and sound regions. In order to quantitatively evaluate the results, the event based F-score is computed. The different information regions of the extracted thermal patterns are considered as different events and the purpose is to objectively evaluate the detectability for different algorithms. Experimental tests and comparative studies have been conducted to prove the efficacy of the proposed method.

Computed laminography and reconstruction algorithm

International Nuclear Information System (INIS)

Que Jiemin; Cao Daquan; Zhao Wei; Tang Xiao

2012-01-01

Computed laminography (CL) is an alternative to computed tomography if large objects are to be inspected with high resolution. This is especially true for planar objects. In this paper, we set up a new scanning geometry for CL, and study the algebraic reconstruction technique (ART) for CL imaging. We compare the results of ART with variant weighted functions by computer simulation with a digital phantom. It proves that ART algorithm is a good choice for the CL system. (authors)

Optimal reservoir operation policies using novel nested algorithms

Science.gov (United States)

Delipetrev, Blagoj; Jonoski, Andreja; Solomatine, Dimitri

2015-04-01

Historically, the two most widely practiced methods for optimal reservoir operation have been dynamic programming (DP) and stochastic dynamic programming (SDP). These two methods suffer from the so called "dual curse" which prevents them to be used in reasonably complex water systems. The first one is the "curse of dimensionality" that denotes an exponential growth of the computational complexity with the state - decision space dimension. The second one is the "curse of modelling" that requires an explicit model of each component of the water system to anticipate the effect of each system's transition. We address the problem of optimal reservoir operation concerning multiple objectives that are related to 1) reservoir releases to satisfy several downstream users competing for water with dynamically varying demands, 2) deviations from the target minimum and maximum reservoir water levels and 3) hydropower production that is a combination of the reservoir water level and the reservoir releases. Addressing such a problem with classical methods (DP and SDP) requires a reasonably high level of discretization of the reservoir storage volume, which in combination with the required releases discretization for meeting the demands of downstream users leads to computationally expensive formulations and causes the curse of dimensionality. We present a novel approach, named "nested" that is implemented in DP, SDP and reinforcement learning (RL) and correspondingly three new algorithms are developed named nested DP (nDP), nested SDP (nSDP) and nested RL (nRL). The nested algorithms are composed from two algorithms: 1) DP, SDP or RL and 2) nested optimization algorithm. Depending on the way we formulate the objective function related to deficits in the allocation problem in the nested optimization, two methods are implemented: 1) Simplex for linear allocation problems, and 2) quadratic Knapsack method in the case of nonlinear problems. The novel idea is to include the nested

Iterative algorithm for reconstructing rotationally asymmetric surface deviation with pixel-level spatial resolution

Science.gov (United States)

Quan, Haiyang; Wu, Fan; Hou, Xi

2015-10-01

New method for reconstructing rotationally asymmetric surface deviation with pixel-level spatial resolution is proposed. It is based on basic iterative scheme and accelerates the Gauss-Seidel method by introducing an acceleration parameter. This modified Successive Over-relaxation (SOR) is effective for solving the rotationally asymmetric components with pixel-level spatial resolution, without the usage of a fitting procedure. Compared to the Jacobi and Gauss-Seidel method, the modified SOR method with an optimal relaxation factor converges much faster and saves more computational costs and memory space without reducing accuracy. It has been proved by real experimental results.

High-definition computed tomography for coronary artery stents imaging: Initial evaluation of the optimal reconstruction algorithm

Energy Technology Data Exchange (ETDEWEB)

Cui, Xiaoming, E-mail: mmayzy2008@126.com; Li, Tao, E-mail: litaofeivip@163.com; Li, Xin, E-mail: lx0803@sina.com.cn; Zhou, Weihua, E-mail: wangxue0606@gmail.com

2015-05-15

Highlights: • High-resolution scan mode is appropriate for imaging coronary stent. • HD-detail reconstruction algorithm is stent-dedicated kernel. • The intrastent lumen visibility also depends on stent diameter and material. - Abstract: Objective: The aim of this study was to evaluate the in vivo performance of four image reconstruction algorithms in a high-definition CT (HDCT) scanner with improved spatial resolution for the evaluation of coronary artery stents and intrastent lumina. Materials and methods: Thirty-nine consecutive patients with a total of 71 implanted coronary stents underwent coronary CT angiography (CCTA) on a HDCT (Discovery CT 750 HD; GE Healthcare) with the high-resolution scanning mode. Four different reconstruction algorithms (HD-stand, HD-detail; HD-stand-plus; HD-detail-plus) were applied to reconstruct the stented coronary arteries. Image quality for stent characterization was assessed. Image noise and intrastent luminal diameter were measured. The relationship between the measurement of inner stent diameter (ISD) and the true stent diameter (TSD) and stent type were analysed. Results: The stent-dedicated kernel (HD-detail) offered the highest percentage (53.5%) of good image quality for stent characterization and the highest ratio (68.0 ± 8.4%) of visible stent lumen/true stent lumen for luminal diameter measurement at the expense of an increased overall image noise. The Pearson correlation coefficient between the ISD and TSD measurement and spearman correlation coefficient between the ISD measurement and stent type were 0.83 and 0.48, respectively. Conclusions: Compared with standard reconstruction algorithms, high-definition CT imaging technique with dedicated high-resolution reconstruction algorithm provides more accurate stent characterization and intrastent luminal diameter measurement.

Contribution to the resolution of algebraic differential equations. Application to electronic circuits and nuclear reactors

International Nuclear Information System (INIS)

Monsef, Youssef.

1977-05-01

This note deals with the resolution of large algebraic differential systems involved in the physical sciences, with special reference to electronics and nuclear physics. The theoretical aspect of the algorithms established and developed for this purpose is discussed in detail. A decomposition algorithm based on the graph theory is developed in detail and the regressive analysis of the error involved in the decomposition is carried out. The specific application of these algorithms on the analyses of non-linear electronic circuits and to the integration of algebraic differential equations simulating the general operation of nuclear reactors coupled to heat exchangers is discussed in detail. To conclude, it is shown that the development of efficient digital resolution techniques dealing with the elements in order is sub-optimal for large systems and calls for the revision of conventional formulation methods. Thus for a high-order physical system, the larger, the number of auxiliary unknowns introduced, the easier the formulation and resolution, owing to the elimination of any form of complex matricial calculation such as those given by the state variables method [fr

Algorithmic randomness and physical entropy

International Nuclear Information System (INIS)

Zurek, W.H.

1989-01-01

Algorithmic randomness provides a rigorous, entropylike measure of disorder of an individual, microscopic, definite state of a physical system. It is defined by the size (in binary digits) of the shortest message specifying the microstate uniquely up to the assumed resolution. Equivalently, algorithmic randomness can be expressed as the number of bits in the smallest program for a universal computer that can reproduce the state in question (for instance, by plotting it with the assumed accuracy). In contrast to the traditional definitions of entropy, algorithmic randomness can be used to measure disorder without any recourse to probabilities. Algorithmic randomness is typically very difficult to calculate exactly but relatively easy to estimate. In large systems, probabilistic ensemble definitions of entropy (e.g., coarse-grained entropy of Gibbs and Boltzmann's entropy H=lnW, as well as Shannon's information-theoretic entropy) provide accurate estimates of the algorithmic entropy of an individual system or its average value for an ensemble. One is thus able to rederive much of thermodynamics and statistical mechanics in a setting very different from the usual. Physical entropy, I suggest, is a sum of (i) the missing information measured by Shannon's formula and (ii) of the algorithmic information content---algorithmic randomness---present in the available data about the system. This definition of entropy is essential in describing the operation of thermodynamic engines from the viewpoint of information gathering and using systems. These Maxwell demon-type entities are capable of acquiring and processing information and therefore can ''decide'' on the basis of the results of their measurements and computations the best strategy for extracting energy from their surroundings. From their internal point of view the outcome of each measurement is definite

An Analysis of Light Periods of BL Lac Object S5 0716+714 with the MUSIC Algorithm

Science.gov (United States)

Tang, Jie

2012-07-01

The multiple signal classification (MUSIC) algorithm is introduced to the estimation of light periods of BL Lac objects. The principle of the MUSIC algorithm is given, together with a testing on its spectral resolution by using a simulative signal. From a lot of literature, we have collected a large number of effective observational data of the BL Lac object S5 0716+714 in the three optical wavebands V, R, and I from 1994 to 2008. The light periods of S5 0716+714 are obtained by means of the MUSIC algorithm and average periodogram algorithm, respectively. It is found that there exist two major periodic components, one is the period of (3.33±0.08) yr, another is the period of (1.24±0.01) yr. The comparison of the performances of periodicity analysis of two algorithms indicates that the MUSIC algorithm has a smaller requirement on the sample length, as well as a good spectral resolution and anti-noise ability, to improve the accuracy of periodicity analysis in the case of short sample length.

Fast iterative segmentation of high resolution medical images

International Nuclear Information System (INIS)

Hebert, T.J.

1996-01-01

Various applications in positron emission tomography (PET), single photon emission computed tomography (SPECT) and magnetic resonance imaging (MRI) require segmentation of 20 to 60 high resolution images of size 256x256 pixels in 3-9 seconds per image. This places particular constraints on the design of image segmentation algorithms. This paper examines the trade-offs in segmenting images based on fitting a density function to the pixel intensities using curve-fitting versus the maximum likelihood method. A quantized data representation is proposed and the EM algorithm for fitting a finite mixture density function to the quantized representation for an image is derived. A Monte Carlo evaluation of mean estimation error and classification error showed that the resulting quantized EM algorithm dramatically reduces the required computation time without loss of accuracy

A new linear back projection algorithm to electrical tomography based on measuring data decomposition

Science.gov (United States)

Sun, Benyuan; Yue, Shihong; Cui, Ziqiang; Wang, Huaxiang

2015-12-01

As an advanced measurement technique of non-radiant, non-intrusive, rapid response, and low cost, the electrical tomography (ET) technique has developed rapidly in recent decades. The ET imaging algorithm plays an important role in the ET imaging process. Linear back projection (LBP) is the most used ET algorithm due to its advantages of dynamic imaging process, real-time response, and easy realization. But the LBP algorithm is of low spatial resolution due to the natural ‘soft field’ effect and ‘ill-posed solution’ problems; thus its applicable ranges are greatly limited. In this paper, an original data decomposition method is proposed, and every ET measuring data are decomposed into two independent new data based on the positive and negative sensing areas of the measuring data. Consequently, the number of total measuring data is extended to twice as many as the number of the original data, thus effectively reducing the ‘ill-posed solution’. On the other hand, an index to measure the ‘soft field’ effect is proposed. The index shows that the decomposed data can distinguish between different contributions of various units (pixels) for any ET measuring data, and can efficiently reduce the ‘soft field’ effect of the ET imaging process. In light of the data decomposition method, a new linear back projection algorithm is proposed to improve the spatial resolution of the ET image. A series of simulations and experiments are applied to validate the proposed algorithm by the real-time performances and the progress of spatial resolutions.

A new linear back projection algorithm to electrical tomography based on measuring data decomposition

International Nuclear Information System (INIS)

Sun, Benyuan; Yue, Shihong; Cui, Ziqiang; Wang, Huaxiang

2015-01-01

As an advanced measurement technique of non-radiant, non-intrusive, rapid response, and low cost, the electrical tomography (ET) technique has developed rapidly in recent decades. The ET imaging algorithm plays an important role in the ET imaging process. Linear back projection (LBP) is the most used ET algorithm due to its advantages of dynamic imaging process, real-time response, and easy realization. But the LBP algorithm is of low spatial resolution due to the natural ‘soft field’ effect and ‘ill-posed solution’ problems; thus its applicable ranges are greatly limited. In this paper, an original data decomposition method is proposed, and every ET measuring data are decomposed into two independent new data based on the positive and negative sensing areas of the measuring data. Consequently, the number of total measuring data is extended to twice as many as the number of the original data, thus effectively reducing the ‘ill-posed solution’. On the other hand, an index to measure the ‘soft field’ effect is proposed. The index shows that the decomposed data can distinguish between different contributions of various units (pixels) for any ET measuring data, and can efficiently reduce the ‘soft field’ effect of the ET imaging process. In light of the data decomposition method, a new linear back projection algorithm is proposed to improve the spatial resolution of the ET image. A series of simulations and experiments are applied to validate the proposed algorithm by the real-time performances and the progress of spatial resolutions. (paper)

Deconvolution of 2D coincident Doppler broadening spectroscopy using the Richardson-Lucy algorithm

International Nuclear Information System (INIS)

Zhang, J.D.; Zhou, T.J.; Cheung, C.K.; Beling, C.D.; Fung, S.; Ng, M.K.

2006-01-01

Coincident Doppler Broadening Spectroscopy (CDBS) measurements are popular in positron solid-state studies of materials. By utilizing the instrumental resolution function obtained from a gamma line close in energy to the 511 keV annihilation line, it is possible to significantly enhance the quality of the CDBS spectra using deconvolution algorithms. In this paper, we compare two algorithms, namely the Non-Negativity Least Squares (NNLS) regularized method and the Richardson-Lucy (RL) algorithm. The latter, which is based on the method of maximum likelihood, is found to give superior results to the regularized least-squares algorithm and with significantly less computer processing time

PixTrig: a Level 2 track finding algorithm based on pixel detector

CERN Document Server

Baratella, A; Morettini, P; Parodi, F

2000-01-01

This note describes an algorithm for track search at Level 2 based on pixel detector. Using three pixel clusters we can produce a reconstruction of the track parameter in both z and R-phi plane. These track segments can be used as seed for more sophisticated track finding algorithms or used directly, especially when impact parameter resolution is crucial. The algorithm efficiency is close to 90% for pt > 1 GeV/c and the processing time is small enough to allow a complete detector reconstruction (non RoI guided) within the Level 2 processing.

Trajectory Evaluation of Rotor-Flying Robots Using Accurate Inverse Computation Based on Algorithm Differentiation

Directory of Open Access Journals (Sweden)

Yuqing He

2014-01-01

Full Text Available Autonomous maneuvering flight control of rotor-flying robots (RFR is a challenging problem due to the highly complicated structure of its model and significant uncertainties regarding many aspects of the field. As a consequence, it is difficult in many cases to decide whether or not a flight maneuver trajectory is feasible. It is necessary to conduct an analysis of the flight maneuvering ability of an RFR prior to test flight. Our aim in this paper is to use a numerical method called algorithm differentiation (AD to solve this problem. The basic idea is to compute the internal state (i.e., attitude angles and angular rates and input profiles based on predetermined maneuvering trajectory information denoted by the outputs (i.e., positions and yaw angle and their higher-order derivatives. For this purpose, we first present a model of the RFR system and show that it is flat. We then cast the procedure for obtaining the required state/input based on the desired outputs as a static optimization problem, which is solved using AD and a derivative based optimization algorithm. Finally, we test our proposed method using a flight maneuver trajectory to verify its performance.

Multiple-image hiding using super resolution reconstruction in high-frequency domains

Science.gov (United States)

Li, Xiao-Wei; Zhao, Wu-Xiang; Wang, Jun; Wang, Qiong-Hua

2017-12-01

In this paper, a robust multiple-image hiding method using the computer-generated integral imaging and the modified super-resolution reconstruction algorithm is proposed. In our work, the host image is first transformed into frequency domains by cellular automata (CA), to assure the quality of the stego-image, the secret images are embedded into the CA high-frequency domains. The proposed method has the following advantages: (1) robustness to geometric attacks because of the memory-distributed property of elemental images, (2) increasing quality of the reconstructed secret images as the scheme utilizes the modified super-resolution reconstruction algorithm. The simulation results show that the proposed multiple-image hiding method outperforms other similar hiding methods and is robust to some geometric attacks, e.g., Gaussian noise and JPEG compression attacks.

High-speed cell recognition algorithm for ultrafast flow cytometer imaging system

Science.gov (United States)

Zhao, Wanyue; Wang, Chao; Chen, Hongwei; Chen, Minghua; Yang, Sigang

2018-04-01

An optical time-stretch flow imaging system enables high-throughput examination of cells/particles with unprecedented high speed and resolution. A significant amount of raw image data is produced. A high-speed cell recognition algorithm is, therefore, highly demanded to analyze large amounts of data efficiently. A high-speed cell recognition algorithm consisting of two-stage cascaded detection and Gaussian mixture model (GMM) classification is proposed. The first stage of detection extracts cell regions. The second stage integrates distance transform and the watershed algorithm to separate clustered cells. Finally, the cells detected are classified by GMM. We compared the performance of our algorithm with support vector machine. Results show that our algorithm increases the running speed by over 150% without sacrificing the recognition accuracy. This algorithm provides a promising solution for high-throughput and automated cell imaging and classification in the ultrafast flow cytometer imaging platform.

Signal Amplification Technique (SAT): an approach for improving resolution and reducing image noise in computed tomography

International Nuclear Information System (INIS)

Phelps, M.E.; Huang, S.C.; Hoffman, E.J.; Plummer, D.; Carson, R.

1981-01-01

Spatial resolution improvements in computed tomography (CT) have been limited by the large and unique error propagation properties of this technique. The desire to provide maximum image resolution has resulted in the use of reconstruction filter functions designed to produce tomographic images with resolution as close as possible to the intrinsic detector resolution. Thus, many CT systems produce images with excessive noise with the system resolution determined by the detector resolution rather than the reconstruction algorithm. CT is a rigorous mathematical technique which applies an increasing amplification to increasing spatial frequencies in the measured data. This mathematical approach to spatial frequency amplification cannot distinguish between signal and noise and therefore both are amplified equally. We report here a method in which tomographic resolution is improved by using very small detectors to selectively amplify the signal and not noise. Thus, this approach is referred to as the signal amplification technique (SAT). SAT can provide dramatic improvements in image resolution without increases in statistical noise or dose because increases in the cutoff frequency of the reconstruction algorithm are not required to improve image resolution. Alternatively, in cases where image counts are low, such as in rapid dynamic or receptor studies, statistical noise can be reduced by lowering the cutoff frequency while still maintaining the best possible image resolution. A possible system design for a positron CT system with SAT is described

FPGA Online Tracking Algorithm for the PANDA Straw Tube Tracker

Science.gov (United States)

Liang, Yutie; Ye, Hua; Galuska, Martin J.; Gessler, Thomas; Kuhn, Wolfgang; Lange, Jens Soren; Wagner, Milan N.; Liu, Zhen'an; Zhao, Jingzhou

2017-06-01

A novel FPGA based online tracking algorithm for helix track reconstruction in a solenoidal field, developed for the PANDA spectrometer, is described. Employing the Straw Tube Tracker detector with 4636 straw tubes, the algorithm includes a complex track finder, and a track fitter. Implemented in VHDL, the algorithm is tested on a Xilinx Virtex-4 FX60 FPGA chip with different types of events, at different event rates. A processing time of 7 $\\mu$s per event for an average of 6 charged tracks is obtained. The momentum resolution is about 3\\% (4\\%) for $p_t$ ($p_z$) at 1 GeV/c. Comparing to the algorithm running on a CPU chip (single core Intel Xeon E5520 at 2.26 GHz), an improvement of 3 orders of magnitude in processing time is obtained. The algorithm can handle severe overlapping of events which are typical for interaction rates above 10 MHz.

The optimal algorithm for Multi-source RS image fusion.

Science.gov (United States)

Fu, Wei; Huang, Shui-Guang; Li, Zeng-Shun; Shen, Hao; Li, Jun-Shuai; Wang, Peng-Yuan

2016-01-01

In order to solve the issue which the fusion rules cannot be self-adaptively adjusted by using available fusion methods according to the subsequent processing requirements of Remote Sensing (RS) image, this paper puts forward GSDA (genetic-iterative self-organizing data analysis algorithm) by integrating the merit of genetic arithmetic together with the advantage of iterative self-organizing data analysis algorithm for multi-source RS image fusion. The proposed algorithm considers the wavelet transform of the translation invariance as the model operator, also regards the contrast pyramid conversion as the observed operator. The algorithm then designs the objective function by taking use of the weighted sum of evaluation indices, and optimizes the objective function by employing GSDA so as to get a higher resolution of RS image. As discussed above, the bullet points of the text are summarized as follows.•The contribution proposes the iterative self-organizing data analysis algorithm for multi-source RS image fusion.•This article presents GSDA algorithm for the self-adaptively adjustment of the fusion rules.•This text comes up with the model operator and the observed operator as the fusion scheme of RS image based on GSDA. The proposed algorithm opens up a novel algorithmic pathway for multi-source RS image fusion by means of GSDA.

Study of position resolution for cathode readout MWPC with measurement of induced charge distribution

International Nuclear Information System (INIS)

Chiba, J.; Iwasaki, H.; Kageyama, T.; Kuribayashi, S.; Nakamura, K.; Sumiyoshi, T.; Takeda, T.

1983-01-01

A readout technqiue of multiwire proportional chambers by measurement of charges induced on cathode strips, orthogonal to anode wires, requires an algorithm to relate the measured charge distribution to the avalanche position. With given chamber parameters and under the influence of noise, resolution limits depend on the chosen algorithm. We have studied the position resolution obtained by the centroid method and by the charge-ratio method, both using three consecutive cathode strips. While the centroid method uses a single number, the center of gravity of the measured charges, the charge-ratio method uses the ratios of the charges Qsub(i-1)/Qsub(i) and Qsub(i+1)/Qsub(i) where Qsub(i) is the largest. To obtain a given resolution, the charge-ratio method generally allows wider cathode strips and therefore a smaller number of readout channels than the centroid method. (orig.)

Short-Term Wind Electric Power Forecasting Using a Novel Multi-Stage Intelligent Algorithm

Directory of Open Access Journals (Sweden)

Haoran Zhao

2018-03-01

Full Text Available As the most efficient renewable energy source for generating electricity in a modern electricity network, wind power has the potential to realize sustainable energy supply. However, owing to its random and intermittent instincts, a high permeability of wind power into a power network demands accurate and effective wind energy prediction models. This study proposes a multi-stage intelligent algorithm for wind electric power prediction, which combines the Beveridge–Nelson (B-N decomposition approach, the Least Square Support Vector Machine (LSSVM, and a newly proposed intelligent optimization approach called the Grasshopper Optimization Algorithm (GOA. For data preprocessing, the B-N decomposition approach was employed to disintegrate the hourly wind electric power data into a deterministic trend, a cyclic term, and a random component. Then, the LSSVM optimized by the GOA (denoted GOA-LSSVM was applied to forecast the future 168 h of the deterministic trend, the cyclic term, and the stochastic component, respectively. Finally, the future hourly wind electric power values can be obtained by multiplying the forecasted values of these three trends. Through comparing the forecasting performance of this proposed method with the LSSVM, the LSSVM optimized by the Fruit-fly Optimization Algorithm (FOA-LSSVM, and the LSSVM optimized by Particle Swarm Optimization (PSO-LSSVM, it is verified that the established multi-stage approach is superior to other models and can increase the precision of wind electric power prediction effectively.

HYBRID OPTIMIZATION OF OBJECT-BASED CLASSIFICATION IN HIGH-RESOLUTION IMAGES USING CONTINOUS ANT COLONY ALGORITHM WITH EMPHASIS ON BUILDING DETECTION

Directory of Open Access Journals (Sweden)

E. Tamimi

2017-09-01

Full Text Available Automatic building detection from High Spatial Resolution (HSR images is one of the most important issues in Remote Sensing (RS. Due to the limited number of spectral bands in HSR images, using other features will lead to improve accuracy. By adding these features, the presence probability of dependent features will be increased, which leads to accuracy reduction. In addition, some parameters should be determined in Support Vector Machine (SVM classification. Therefore, it is necessary to simultaneously determine classification parameters and select independent features according to image type. Optimization algorithm is an efficient method to solve this problem. On the other hand, pixel-based classification faces several challenges such as producing salt-paper results and high computational time in high dimensional data. Hence, in this paper, a novel method is proposed to optimize object-based SVM classification by applying continuous Ant Colony Optimization (ACO algorithm. The advantages of the proposed method are relatively high automation level, independency of image scene and type, post processing reduction for building edge reconstruction and accuracy improvement. The proposed method was evaluated by pixel-based SVM and Random Forest (RF classification in terms of accuracy. In comparison with optimized pixel-based SVM classification, the results showed that the proposed method improved quality factor and overall accuracy by 17% and 10%, respectively. Also, in the proposed method, Kappa coefficient was improved by 6% rather than RF classification. Time processing of the proposed method was relatively low because of unit of image analysis (image object. These showed the superiority of the proposed method in terms of time and accuracy.

Enhancing resolution and contrast in second-harmonic generation microscopy using an advanced maximum likelihood estimation restoration method

Science.gov (United States)

Sivaguru, Mayandi; Kabir, Mohammad M.; Gartia, Manas Ranjan; Biggs, David S. C.; Sivaguru, Barghav S.; Sivaguru, Vignesh A.; Berent, Zachary T.; Wagoner Johnson, Amy J.; Fried, Glenn A.; Liu, Gang Logan; Sadayappan, Sakthivel; Toussaint, Kimani C.

2017-02-01

Second-harmonic generation (SHG) microscopy is a label-free imaging technique to study collagenous materials in extracellular matrix environment with high resolution and contrast. However, like many other microscopy techniques, the actual spatial resolution achievable by SHG microscopy is reduced by out-of-focus blur and optical aberrations that degrade particularly the amplitude of the detectable higher spatial frequencies. Being a two-photon scattering process, it is challenging to define a point spread function (PSF) for the SHG imaging modality. As a result, in comparison with other two-photon imaging systems like two-photon fluorescence, it is difficult to apply any PSF-engineering techniques to enhance the experimental spatial resolution closer to the diffraction limit. Here, we present a method to improve the spatial resolution in SHG microscopy using an advanced maximum likelihood estimation (AdvMLE) algorithm to recover the otherwise degraded higher spatial frequencies in an SHG image. Through adaptation and iteration, the AdvMLE algorithm calculates an improved PSF for an SHG image and enhances the spatial resolution by decreasing the full-width-at-halfmaximum (FWHM) by 20%. Similar results are consistently observed for biological tissues with varying SHG sources, such as gold nanoparticles and collagen in porcine feet tendons. By obtaining an experimental transverse spatial resolution of 400 nm, we show that the AdvMLE algorithm brings the practical spatial resolution closer to the theoretical diffraction limit. Our approach is suitable for adaptation in micro-nano CT and MRI imaging, which has the potential to impact diagnosis and treatment of human diseases.

Towards Compatible and Interderivable Semantic Specifications for the Scheme Programming Language, Part I: Denotational Semantics, Natural Semantics, and Abstract Machines

DEFF Research Database (Denmark)

Danvy, Olivier

2008-01-01

We derive two big-step abstract machines, a natural semantics, and the valuation function of a denotational semantics based on the small-step abstract machine for Core Scheme presented by Clinger at PLDI'98. Starting from a functional implementation of this small-step abstract machine, (1) we fuse...... its transition function with its driver loop, obtaining the functional implementation of a big-step abstract machine; (2) we adjust this big-step abstract machine so that it is in defunctionalized form, obtaining the functional implementation of a second big-step abstract machine; (3) we...... refunctionalize this adjusted abstract machine, obtaining the functional implementation of a natural semantics in continuation style; and (4) we closure-unconvert this natural semantics, obtaining a compositional continuation-passing evaluation function which we identify as the functional implementation...

Limits of a spatial resolution of the cascaded GEM based detectors

International Nuclear Information System (INIS)

Kudryavtsev, V.N.; Maltsev, T.V.; Shekhtman, L.I.

2017-01-01

Spatial resolution of tracking detectors based on GEM cascades is determined in the simulation and measured. The simulation includes GEANT4 implemented transport of high energy electrons with careful accounting for atomic relaxation processes including emission of fluorescent photons and Auger electrons and custom post-processing taking into account diffusion, gas amplification fluctuations, the distribution of signals over readout electrodes, electronics noise and particular algorithm of final coordinate calculation (centre-of-gravity algorithm). The simulation demonstrates that the minimum of the spatial resolution of about 10–20 μm can be achieved with a gas mixture of Ar-CO 2 (75%–25%) at a strip pitch in the range from 250 μm to 300 μm. At a larger pitch the resolution quickly degrades reaching 70–100 μm at a pitch of 450–500 μm. The reasons of such behavior are discussed and corresponding hypothesis is tested. Particularly, the effect of electron cloud modification due to a GEM operation is considered using the ANSYS and Garfield++ simulation programs. The detection efficiency and spatial resolution of low-material triple-GEM detectors for the DEUTERON facility at BINP are measured at the extracted beam facility of the VEPP-4M collider. One-coordinate resolution of two detectors for the DEUTERON facility is measured with a 2 GeV electron beam. The determined values of the detectors' spatial resolution is equal to 46.6 ± 0.1 μm and 38.5 ± 0.2 μm for orthogonal tracks in two detectors, respectively.

Limits of a spatial resolution of the cascaded GEM based detectors

Science.gov (United States)

Kudryavtsev, V. N.; Maltsev, T. V.; Shekhtman, L. I.

2017-06-01

Spatial resolution of tracking detectors based on GEM cascades is determined in the simulation and measured. The simulation includes GEANT4 implemented transport of high energy electrons with careful accounting for atomic relaxation processes including emission of fluorescent photons and Auger electrons and custom post-processing taking into account diffusion, gas amplification fluctuations, the distribution of signals over readout electrodes, electronics noise and particular algorithm of final coordinate calculation (centre-of-gravity algorithm). The simulation demonstrates that the minimum of the spatial resolution of about 10-20 μm can be achieved with a gas mixture of Ar-CO2 (75%-25%) at a strip pitch in the range from 250 μm to 300 μm. At a larger pitch the resolution quickly degrades reaching 70-100 μm at a pitch of 450-500 μm. The reasons of such behavior are discussed and corresponding hypothesis is tested. Particularly, the effect of electron cloud modification due to a GEM operation is considered using the ANSYS and Garfield++ simulation programs. The detection efficiency and spatial resolution of low-material triple-GEM detectors for the DEUTERON facility at BINP are measured at the extracted beam facility of the VEPP-4M collider. One-coordinate resolution of two detectors for the DEUTERON facility is measured with a 2 GeV electron beam. The determined values of the detectors' spatial resolution is equal to 46.6 ± 0.1 μm and 38.5 ± 0.2 μm for orthogonal tracks in two detectors, respectively.

Introduction to the virtual special issue on super-resolution imaging techniques

Science.gov (United States)

Cao, Liangcai; Liu, Zhengjun

2017-12-01

Until quite recently, the resolution of optical imaging instruments, including telescopes, cameras and microscopes, was considered to be limited by the diffraction of light and by image sensors. In the past few years, many exciting super-resolution approaches have emerged that demonstrate intriguing ways to bypass the classical limit in optics and detectors. More and more research groups are engaged in the study of advanced super-resolution schemes, devices, algorithms, systems, and applications [1-6]. Super-resolution techniques involve new methods in science and engineering of optics [7,8], measurements [9,10], chemistry [11,12] and information [13,14]. Promising applications, particularly in biomedical research and semiconductor industry, have been successfully demonstrated.

High spatial resolution CT image reconstruction using parallel computing

International Nuclear Information System (INIS)

Yin Yin; Liu Li; Sun Gongxing

2003-01-01

Using the PC cluster system with 16 dual CPU nodes, we accelerate the FBP and OR-OSEM reconstruction of high spatial resolution image (2048 x 2048). Based on the number of projections, we rewrite the reconstruction algorithms into parallel format and dispatch the tasks to each CPU. By parallel computing, the speedup factor is roughly equal to the number of CPUs, which can be up to about 25 times when 25 CPUs used. This technique is very suitable for real-time high spatial resolution CT image reconstruction. (authors)

Deep Learning based Super-Resolution for Improved Action Recognition

DEFF Research Database (Denmark)

Nasrollahi, Kamal; Guerrero, Sergio Escalera; Rasti, Pejman

2015-01-01

with results of a state-of- the-art deep learning-based super-resolution algorithm, through an alpha-blending approach. The experimental results obtained on down-sampled version of a large subset of Hoolywood2 benchmark database show the importance of the proposed system in increasing the recognition rate...

An Improved Phase Gradient Autofocus Algorithm Used in Real-time Processing

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Qing Ji-ming

2015-10-01

Full Text Available The Phase Gradient Autofocus (PGA algorithm can remove the high order phase error effectively, which is of great significance to get high resolution images in real-time processing. While PGA usually needs iteration, which necessitates long working hours. In addition, the performances of the algorithm are not stable in different scene applications. This severely constrains the application of PGA in real-time processing. Isolated scatter selection and windowing are two important algorithmic steps of Phase Gradient Autofocus Algorithm. Therefore, this paper presents an isolated scatter selection method based on sample mean and a windowing method based on pulse envelope. These two methods are highly adaptable to data, which would make the algorithm obtain better stability and need less iteration. The adaptability of the improved PGA is demonstrated with the experimental results of real radar data.

Performance Evaluations for Super-Resolution Mosaicing on UAS Surveillance Videos

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Aldo Camargo

2013-05-01

Full Text Available Abstract Unmanned Aircraft Systems (UAS have been widely applied for reconnaissance and surveillance by exploiting information collected from the digital imaging payload. The super-resolution (SR mosaicing of low-resolution (LR UAS surveillance video frames has become a critical requirement for UAS video processing and is important for further effective image understanding. In this paper we develop a novel super-resolution framework, which does not require the construction of sparse matrices. The proposed method implements image operations in the spatial domain and applies an iterated back-projection to construct super-resolution mosaics from the overlapping UAS surveillance video frames. The Steepest Descent method, the Conjugate Gradient method and the Levenberg-Marquardt algorithm are used to numerically solve the nonlinear optimization problem for estimating a super-resolution mosaic. A quantitative performance comparison in terms of computation time and visual quality of the super-resolution mosaics through the three numerical techniques is presented.

An advanced algorithm for deformation estimation in non-urban areas

Science.gov (United States)

Goel, Kanika; Adam, Nico

2012-09-01

This paper presents an advanced differential SAR interferometry stacking algorithm for high resolution deformation monitoring in non-urban areas with a focus on distributed scatterers (DSs). Techniques such as the Small Baseline Subset Algorithm (SBAS) have been proposed for processing DSs. SBAS makes use of small baseline differential interferogram subsets. Singular value decomposition (SVD), i.e. L2 norm minimization is applied to link independent subsets separated by large baselines. However, the interferograms used in SBAS are multilooked using a rectangular window to reduce phase noise caused for instance by temporal decorrelation, resulting in a loss of resolution and the superposition of topography and deformation signals from different objects. Moreover, these have to be individually phase unwrapped and this can be especially difficult in natural terrains. An improved deformation estimation technique is presented here which exploits high resolution SAR data and is suitable for rural areas. The implemented method makes use of small baseline differential interferograms and incorporates an object adaptive spatial phase filtering and residual topography removal for an accurate phase and coherence estimation, while preserving the high resolution provided by modern satellites. This is followed by retrieval of deformation via the SBAS approach, wherein, the phase inversion is performed using an L1 norm minimization which is more robust to the typical phase unwrapping errors encountered in non-urban areas. Meter resolution TerraSAR-X data of an underground gas storage reservoir in Germany is used for demonstrating the effectiveness of this newly developed technique in rural areas.

Large-scale runoff generation - parsimonious parameterisation using high-resolution topography

Science.gov (United States)

Gong, L.; Halldin, S.; Xu, C.-Y.

2011-08-01

World water resources have primarily been analysed by global-scale hydrological models in the last decades. Runoff generation in many of these models are based on process formulations developed at catchments scales. The division between slow runoff (baseflow) and fast runoff is primarily governed by slope and spatial distribution of effective water storage capacity, both acting at very small scales. Many hydrological models, e.g. VIC, account for the spatial storage variability in terms of statistical distributions; such models are generally proven to perform well. The statistical approaches, however, use the same runoff-generation parameters everywhere in a basin. The TOPMODEL concept, on the other hand, links the effective maximum storage capacity with real-world topography. Recent availability of global high-quality, high-resolution topographic data makes TOPMODEL attractive as a basis for a physically-based runoff-generation algorithm at large scales, even if its assumptions are not valid in flat terrain or for deep groundwater systems. We present a new runoff-generation algorithm for large-scale hydrology based on TOPMODEL concepts intended to overcome these problems. The TRG (topography-derived runoff generation) algorithm relaxes the TOPMODEL equilibrium assumption so baseflow generation is not tied to topography. TRG only uses the topographic index to distribute average storage to each topographic index class. The maximum storage capacity is proportional to the range of topographic index and is scaled by one parameter. The distribution of storage capacity within large-scale grid cells is obtained numerically through topographic analysis. The new topography-derived distribution function is then inserted into a runoff-generation framework similar VIC's. Different basin parts are parameterised by different storage capacities, and different shapes of the storage-distribution curves depend on their topographic characteristics. The TRG algorithm is driven by the

A fast algorithm for computer aided collimation gamma camera (CACAO)

Science.gov (United States)

Jeanguillaume, C.; Begot, S.; Quartuccio, M.; Douiri, A.; Franck, D.; Pihet, P.; Ballongue, P.

2000-08-01

The computer aided collimation gamma camera is aimed at breaking down the resolution sensitivity trade-off of the conventional parallel hole collimator. It uses larger and longer holes, having an added linear movement at the acquisition sequence. A dedicated algorithm including shift and sum, deconvolution, parabolic filtering and rotation is described. Examples of reconstruction are given. This work shows that a simple and fast algorithm, based on a diagonal dominant approximation of the problem can be derived. Its gives a practical solution to the CACAO reconstruction problem.

Multi-GPU Accelerated Admittance Method for High-Resolution Human Exposure Evaluation.

Science.gov (United States)

Xiong, Zubiao; Feng, Shi; Kautz, Richard; Chandra, Sandeep; Altunyurt, Nevin; Chen, Ji

2015-12-01

A multi-graphics processing unit (GPU) accelerated admittance method solver is presented for solving the induced electric field in high-resolution anatomical models of human body when exposed to external low-frequency magnetic fields. In the solver, the anatomical model is discretized as a three-dimensional network of admittances. The conjugate orthogonal conjugate gradient (COCG) iterative algorithm is employed to take advantage of the symmetric property of the complex-valued linear system of equations. Compared against the widely used biconjugate gradient stabilized method, the COCG algorithm can reduce the solving time by 3.5 times and reduce the storage requirement by about 40%. The iterative algorithm is then accelerated further by using multiple NVIDIA GPUs. The computations and data transfers between GPUs are overlapped in time by using asynchronous concurrent execution design. The communication overhead is well hidden so that the acceleration is nearly linear with the number of GPU cards. Numerical examples show that our GPU implementation running on four NVIDIA Tesla K20c cards can reach 90 times faster than the CPU implementation running on eight CPU cores (two Intel Xeon E5-2603 processors). The implemented solver is able to solve large dimensional problems efficiently. A whole adult body discretized in 1-mm resolution can be solved in just several minutes. The high efficiency achieved makes it practical to investigate human exposure involving a large number of cases with a high resolution that meets the requirements of international dosimetry guidelines.

Discriminating Phytoplankton Functional Types (PFTs) in the Coastal Ocean Using the Inversion Algorithm Phydotax and Airborne Imaging Spectrometer Data

Science.gov (United States)

Palacios, Sherry L.; Schafer, Chris; Broughton, Jennifer; Guild, Liane S.; Kudela, Raphael M.

2013-01-01

There is a need in the Biological Oceanography community to discriminate among phytoplankton groups within the bulk chlorophyll pool to understand energy flow through ecosystems, to track the fate of carbon in the ocean, and to detect and monitor-for harmful algal blooms (HABs). The ocean color community has responded to this demand with the development of phytoplankton functional type (PFT) discrimination algorithms. These PFT algorithms fall into one of three categories depending on the science application: size-based, biogeochemical function, and taxonomy. The new PFT algorithm Phytoplankton Detection with Optics (PHYDOTax) is an inversion algorithm that discriminates taxon-specific biomass to differentiate among six taxa found in the California Current System: diatoms, dinoflagellates, haptophytes, chlorophytes, cryptophytes, and cyanophytes. PHYDOTax was developed and validated in Monterey Bay, CA for the high resolution imaging spectrometer, Spectroscopic Aerial Mapping System with On-board Navigation (SAMSON - 3.5 nm resolution). PHYDOTax exploits the high spectral resolution of an imaging spectrometer and the improved spatial resolution that airborne data provides for coastal areas. The objective of this study was to apply PHYDOTax to a relatively lower resolution imaging spectrometer to test the algorithm's sensitivity to atmospheric correction, to evaluate capability with other sensors, and to determine if down-sampling spectral resolution would degrade its ability to discriminate among phytoplankton taxa. This study is a part of the larger Hyperspectral Infrared Imager (HyspIRI) airborne simulation campaign which is collecting Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imagery aboard NASA's ER-2 aircraft during three seasons in each of two years over terrestrial and marine targets in California. Our aquatic component seeks to develop and test algorithms to retrieve water quality properties (e.g. HABs and river plumes) in both marine and in

Second-order accurate volume-of-fluid algorithms for tracking material interfaces

International Nuclear Information System (INIS)

Pilliod, James Edward; Puckett, Elbridge Gerry

2004-01-01

We introduce two new volume-of-fluid interface reconstruction algorithms and compare the accuracy of these algorithms to four other widely used volume-of-fluid interface reconstruction algorithms. We find that when the interface is smooth (e.g., continuous with two continuous derivatives) the new methods are second-order accurate and the other algorithms are first-order accurate. We propose a design criteria for a volume-of-fluid interface reconstruction algorithm to be second-order accurate. Namely, that it reproduce lines in two space dimensions or planes in three space dimensions exactly. We also introduce a second-order, unsplit, volume-of-fluid advection algorithm that is based on a second-order, finite difference method for scalar conservation laws due to Bell, Dawson and Shubin. We test this advection algorithm by modeling several different interface shapes propagating in two simple incompressible flows and compare the results with the standard second-order, operator-split advection algorithm. Although both methods are second-order accurate when the interface is smooth, we find that the unsplit algorithm exhibits noticeably better resolution in regions where the interface has discontinuous derivatives, such as at corners

Frequency-domain imaging algorithm for ultrasonic testing by application of matrix phased arrays

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Dolmatov Dmitry

2017-01-01

Full Text Available Constantly increasing demand for high-performance materials and systems in aerospace industry requires advanced methods of nondestructive testing. One of the most promising methods is ultrasonic imaging by using matrix phased arrays. This technique allows to create three-dimensional ultrasonic imaging with high lateral resolution. Further progress in matrix phased array ultrasonic testing is determined by the development of fast imaging algorithms. In this article imaging algorithm based on frequency domain calculations is proposed. This approach is computationally efficient in comparison with time domain algorithms. Performance of the proposed algorithm was tested via computer simulations for planar specimen with flat bottom holes.

Assessment of Machine Learning Algorithms for Automatic Benthic Cover Monitoring and Mapping Using Towed Underwater Video Camera and High-Resolution Satellite Images

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Hassan Mohamed

2018-05-01

Full Text Available Benthic habitat monitoring is essential for many applications involving biodiversity, marine resource management, and the estimation of variations over temporal and spatial scales. Nevertheless, both automatic and semi-automatic analytical methods for deriving ecologically significant information from towed camera images are still limited. This study proposes a methodology that enables a high-resolution towed camera with a Global Navigation Satellite System (GNSS to adaptively monitor and map benthic habitats. First, the towed camera finishes a pre-programmed initial survey to collect benthic habitat videos, which can then be converted to geo-located benthic habitat images. Second, an expert labels a number of benthic habitat images to class habitats manually. Third, attributes for categorizing these images are extracted automatically using the Bag of Features (BOF algorithm. Fourth, benthic cover categories are detected automatically using Weighted Majority Voting (WMV ensembles for Support Vector Machines (SVM, K-Nearest Neighbor (K-NN, and Bagging (BAG classifiers. Fifth, WMV-trained ensembles can be used for categorizing more benthic cover images automatically. Finally, correctly categorized geo-located images can provide ground truth samples for benthic cover mapping using high-resolution satellite imagery. The proposed methodology was tested over Shiraho, Ishigaki Island, Japan, a heterogeneous coastal area. The WMV ensemble exhibited 89% overall accuracy for categorizing corals, sediments, seagrass, and algae species. Furthermore, the same WMV ensemble produced a benthic cover map using a Quickbird satellite image with 92.7% overall accuracy.

Extracting a Good Quality Frontal Face Image from a Low-Resolution Video Sequence

DEFF Research Database (Denmark)

Nasrollahi, Kamal; Moeslund, Thomas B.

2011-01-01

Feeding low-resolution and low-quality images, from inexpensive surveillance cameras, to systems like, e.g., face recognition, produces erroneous and unstable results. Therefore, there is a need for a mechanism to bridge the gap between on one hand low-resolution and low-quality images......, we use a learning-based super-resolution algorithm applied to the result of the reconstruction-based part to improve the quality by another factor of two. This results in an improvement factor of four for the entire system. The proposed system has been tested on 122 low-resolution sequences from two...... different databases. The experimental results show that the proposed system can indeed produce a high-resolution and good quality frontal face image from low-resolution video sequences....

Improved algorithm for surface display from volumetric data

International Nuclear Information System (INIS)

Lobregt, S.; Schaars, H.W.G.K.; OpdeBeek, J.C.A.; Zonneveld, F.W.

1988-01-01

A high-resolution surface display is produced from three-dimensional datasets (computed tomography or magnetic resonance imaging). Unlike other voxel-based methods, this algorithm does not show a cuberille surface structure, because the surface orientation is calculated from original gray values. The applied surface shading is a function of local orientation and position of the surface and of a virtual light source, giving a realistic impression of the surface of bone and soft tissue. The projection and shading are table driven, combining variable viewpoint and illumination conditions with speed. Other options are cutplane gray-level display and surface transparency. Combined with volume scanning, this algorithm offers powerful application possibilities

Optimized coincidence Doppler broadening spectroscopy using deconvolution algorithms

International Nuclear Information System (INIS)

Ho, K.F.; Ching, H.M.; Cheng, K.W.; Beling, C.D.; Fung, S.; Ng, K.P.

2004-01-01

In the last few years a number of excellent deconvolution algorithms have been developed for use in ''de-blurring'' 2D images. Here we report briefly on one such algorithm we have studied which uses the non-negativity constraint to optimize the regularization and which is applied to the 2D image like data produced in Coincidence Doppler Broadening Spectroscopy (CDBS). The system instrumental resolution functions are obtained using the 514 keV line from 85 Sr. The technique when applied to a series of well annealed polycrystalline metals gives two photon momentum data on a quality comparable to that obtainable using 1D Angular Correlation of Annihilation Radiation (ACAR). (orig.)

Video game for learning and metaphorization of recursive algorithms

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Ricardo Inacio Alvares Silva

2013-09-01

Full Text Available The learning of recursive algorithms in computer programming is problematic, because its execution and resolution is not natural to the thinking way people are trained and used to since young. As with other topics in algorithms, we use metaphors to make parallels between the abstract and the concrete to help in understanding the operation of recursive algorithms. However, the classic metaphors employed in this area, such as calculating factorial recursively and Towers of Hanoi game, may just confuse more or be insufficient. In this work, we produced a computer game to assist students in computer courses in learning recursive algorithms. It was designed to have regular video game characteristics, with narrative and classical gameplay elements, commonly found in this kind of product. Aiding to education occurs through metaphorization, or in other words, through experiences provided by game situations that refer to recursive algorithms. To this end, we designed and imbued in the game four valid metaphors related to the theory, and other minor references to the subject.

Information content of ozone retrieval algorithms

Science.gov (United States)

Rodgers, C.; Bhartia, P. K.; Chu, W. P.; Curran, R.; Deluisi, J.; Gille, J. C.; Hudson, R.; Mateer, C.; Rusch, D.; Thomas, R. J.

1989-01-01

The algorithms are characterized that were used for production processing by the major suppliers of ozone data to show quantitatively: how the retrieved profile is related to the actual profile (This characterizes the altitude range and vertical resolution of the data); the nature of systematic errors in the retrieved profiles, including their vertical structure and relation to uncertain instrumental parameters; how trends in the real ozone are reflected in trends in the retrieved ozone profile; and how trends in other quantities (both instrumental and atmospheric) might appear as trends in the ozone profile. No serious deficiencies were found in the algorithms used in generating the major available ozone data sets. As the measurements are all indirect in someway, and the retrieved profiles have different characteristics, data from different instruments are not directly comparable.

Effects of pose and image resolution on automatic face recognition

NARCIS (Netherlands)

Mahmood, Zahid; Ali, Tauseef; Khan, Samee U.

The popularity of face recognition systems have increased due to their use in widespread applications. Driven by the enormous number of potential application domains, several algorithms have been proposed for face recognition. Face pose and image resolutions are among the two important factors that

An Efficient Method for Mapping High-Resolution Global River Discharge Based on the Algorithms of Drainage Network Extraction

Directory of Open Access Journals (Sweden)

Jiaye Li

2018-04-01

Full Text Available River discharge, which represents the accumulation of surface water flowing into rivers and ultimately into the ocean or other water bodies, may have great impacts on water quality and the living organisms in rivers. However, the global knowledge of river discharge is still poor and worth exploring. This study proposes an efficient method for mapping high-resolution global river discharge based on the algorithms of drainage network extraction. Using the existing global runoff map and digital elevation model (DEM data as inputs, this method consists of three steps. First, the pixels of the runoff map and the DEM data are resampled into the same resolution (i.e., 0.01-degree. Second, the flow direction of each pixel of the DEM data (identified by the optimal flow path method used in drainage network extraction is determined and then applied to the corresponding pixel of the runoff map. Third, the river discharge of each pixel of the runoff map is calculated by summing the runoffs of all the pixels in the upstream of this pixel, similar to the upslope area accumulation step in drainage network extraction. Finally, a 0.01-degree global map of the mean annual river discharge is obtained. Moreover, a 0.5-degree global map of the mean annual river discharge is produced to display the results with a more intuitive perception. Compared against the existing global river discharge databases, the 0.01-degree map is of a generally high accuracy for the selected river basins, especially for the Amazon River basin with the lowest relative error (RE of 0.3% and the Yangtze River basin within the RE range of ±6.0%. However, it is noted that the results of the Congo and Zambezi River basins are not satisfactory, with RE values over 90%, and it is inferred that there may be some accuracy problems with the runoff map in these river basins.

APPLICATION OF A LATTICE GAS MODEL FOR SUBPIXEL PROCESSING OF LOW-RESOLUTION IMAGES OF BINARY STRUCTURES

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Zbisław Tabor

2011-05-01

Full Text Available In the study an algorithm based on a lattice gas model is proposed as a tool for enhancing quality of lowresolution images of binary structures. Analyzed low-resolution gray-level images are replaced with binary images, in which pixel size is decreased. The intensity in the pixels of these new images is determined by corresponding gray-level intensities in the original low-resolution images. Then the white phase pixels in the binary images are assumed to be particles interacting with one another, interacting with properly defined external field and allowed to diffuse. The evolution is driven towards a state with maximal energy by Metropolis algorithm. This state is used to estimate the imaged object. The performance of the proposed algorithm and local and global thresholding methods are compared.

Are decisions using cost-utility analyses robust to choice of SF-36/SF-12 preference-based algorithm?

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Walton Surrey M

2005-03-01

Full Text Available Abstract Background Cost utility analysis (CUA using SF-36/SF-12 data has been facilitated by the development of several preference-based algorithms. The purpose of this study was to illustrate how decision-making could be affected by the choice of preference-based algorithms for the SF-36 and SF-12, and provide some guidance on selecting an appropriate algorithm. Methods Two sets of data were used: (1 a clinical trial of adult asthma patients; and (2 a longitudinal study of post-stroke patients. Incremental costs were assumed to be $2000 per year over standard treatment, and QALY gains realized over a 1-year period. Ten published algorithms were identified, denoted by first author: Brazier (SF-36, Brazier (SF-12, Shmueli, Fryback, Lundberg, Nichol, Franks (3 algorithms, and Lawrence. Incremental cost-utility ratios (ICURs for each algorithm, stated in dollars per quality-adjusted life year ($/QALY, were ranked and compared between datasets. Results In the asthma patients, estimated ICURs ranged from Lawrence's SF-12 algorithm at $30,769/QALY (95% CI: 26,316 to 36,697 to Brazier's SF-36 algorithm at $63,492/QALY (95% CI: 48,780 to 83,333. ICURs for the stroke cohort varied slightly more dramatically. The MEPS-based algorithm by Franks et al. provided the lowest ICUR at $27,972/QALY (95% CI: 20,942 to 41,667. The Fryback and Shmueli algorithms provided ICURs that were greater than $50,000/QALY and did not have confidence intervals that overlapped with most of the other algorithms. The ICUR-based ranking of algorithms was strongly correlated between the asthma and stroke datasets (r = 0.60. Conclusion SF-36/SF-12 preference-based algorithms produced a wide range of ICURs that could potentially lead to different reimbursement decisions. Brazier's SF-36 and SF-12 algorithms have a strong methodological and theoretical basis and tended to generate relatively higher ICUR estimates, considerations that support a preference for these algorithms over the

Improving Accuracy and Simplifying Training in Fingerprinting-Based Indoor Location Algorithms at Room Level

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Mario Muñoz-Organero

2016-01-01

Full Text Available Fingerprinting-based algorithms are popular in indoor location systems based on mobile devices. Comparing the RSSI (Received Signal Strength Indicator from different radio wave transmitters, such as Wi-Fi access points, with prerecorded fingerprints from located points (using different artificial intelligence algorithms, fingerprinting-based systems can locate unknown points with a few meters resolution. However, training the system with already located fingerprints tends to be an expensive task both in time and in resources, especially if large areas are to be considered. Moreover, the decision algorithms tend to be of high memory and CPU consuming in such cases and so does the required time for obtaining the estimated location for a new fingerprint. In this paper, we study, propose, and validate a way to select the locations for the training fingerprints which reduces the amount of required points while improving the accuracy of the algorithms when locating points at room level resolution. We present a comparison of different artificial intelligence decision algorithms and select those with better results. We do a comparison with other systems in the literature and draw conclusions about the improvements obtained in our proposal. Moreover, some techniques such as filtering nonstable access points for improving accuracy are introduced, studied, and validated.

Multispectral and Panchromatic used Enhancement Resolution and Study Effective Enhancement on Supervised and Unsupervised Classification Land – Cover

Science.gov (United States)

Salman, S. S.; Abbas, W. A.

2018-05-01

The goal of the study is to support analysis Enhancement of Resolution and study effect on classification methods on bands spectral information of specific and quantitative approaches. In this study introduce a method to enhancement resolution Landsat 8 of combining the bands spectral of 30 meters resolution with panchromatic band 8 of 15 meters resolution, because of importance multispectral imagery to extracting land - cover. Classification methods used in this study to classify several lands -covers recorded from OLI- 8 imagery. Two methods of Data mining can be classified as either supervised or unsupervised. In supervised methods, there is a particular predefined target, that means the algorithm learn which values of the target are associated with which values of the predictor sample. K-nearest neighbors and maximum likelihood algorithms examine in this work as supervised methods. In other hand, no sample identified as target in unsupervised methods, the algorithm of data extraction searches for structure and patterns between all the variables, represented by Fuzzy C-mean clustering method as one of the unsupervised methods, NDVI vegetation index used to compare the results of classification method, the percent of dense vegetation in maximum likelihood method give a best results.

Toward robust high resolution fluorescence tomography: a hybrid row-action edge preserving regularization

Science.gov (United States)

Behrooz, Ali; Zhou, Hao-Min; Eftekhar, Ali A.; Adibi, Ali

2011-02-01

Depth-resolved localization and quantification of fluorescence distribution in tissue, called Fluorescence Molecular Tomography (FMT), is highly ill-conditioned as depth information should be extracted from limited number of surface measurements. Inverse solvers resort to regularization algorithms that penalize Euclidean norm of the solution to overcome ill-posedness. While these regularization algorithms offer good accuracy, their smoothing effects result in continuous distributions which lack high-frequency edge-type features of the actual fluorescence distribution and hence limit the resolution offered by FMT. We propose an algorithm that penalizes the total variation (TV) norm of the solution to preserve sharp transitions and high-frequency components in the reconstructed fluorescence map while overcoming ill-posedness. The hybrid algorithm is composed of two levels: 1) An Algebraic Reconstruction Technique (ART), performed on FMT data for fast recovery of a smooth solution that serves as an initial guess for the iterative TV regularization, 2) A time marching TV regularization algorithm, inspired by the Rudin-Osher-Fatemi TV image restoration, performed on the initial guess to further enhance the resolution and accuracy of the reconstruction. The performance of the proposed method in resolving fluorescent tubes inserted in a liquid tissue phantom imaged by a non-contact CW trans-illumination FMT system is studied and compared to conventional regularization schemes. It is observed that the proposed method performs better in resolving fluorescence inclusions at higher depths.

A landscape scale valley confinement algorithm: Delineating unconfined valley bottoms for geomorphic, aquatic, and riparian applications

Science.gov (United States)

David E. Nagel; John M. Buffington; Sharon L. Parkes; Seth Wenger; Jaime R. Goode

2014-01-01

Valley confinement is an important landscape characteristic linked to aquatic habitat, riparian diversity, and geomorphic processes. This report describes a GIS program called the Valley Confinement Algorithm (VCA), which identifies unconfined valleys in montane landscapes. The algorithm uses nationally available digital elevation models (DEMs) at 10-30 m resolution to...

高效超分辨波达方向估计算法综述%Overview of efficient algorithms for super-resolution DOA estimates

Institute of Scientific and Technical Information of China (English)

闫锋刚; 沈毅; 刘帅; 金铭; 乔晓林

2015-01-01

Computationally efficient methods for super-resolution direction of arrival (DOA)estimation aim to reduce the complexity of conventional techniques,to economize on the costs of systems and to enhance the ro-bustness of DOA estimators against array geometries and other environmental restrictions,which has been an important topic in the field.According to the theory and elements of the multiple signal classification (MUSIC) algorithm and the primary derivations from MUSIC,state-of-the-art efficient super-resolution DOA estimators are classified into five different types.These five types of approaches reduce the complexity by real-valued com-putation,beam-space transformation,fast subspace estimation,rapid spectral search,and no spectral search, respectively.With such a classification,comprehensive overviews of each kind of efficient methods are given and numerical comparisons among these estimators are also conducted to illustrate their advantages.Future develop-ment trends of efficient algorithms for super-resolution DOA estimates are finally predicted with basic require-ments of real-world applications.%高效超分辨波达方向估计算法致力于降低超分辨算法的计算量、节约系统的实现成本、弱化算法对于阵列结构的依赖性，是推进超分辨理论工程化的一个重要研究课题。从多重信号分类（multiple signal classifi-cation，MUSIC）算法的原理和构成要素入手，以基于 MUSIC 派生高效超分辨算法的目的和方法为标准，将现存高效超分辨算法划分为实值运算、波束域变换、快速子空间估计、快速峰值搜索和免峰值搜索5大类。在此基础上，全面回顾总结了各类高效算法的发展历程和最新进展，对比分析了它们的主要优缺点。最后，结合空间谱估计实际工程化的应用需求，指出了高效超分辨算法的未来发展趋势。

Genetic Algorithms: A New Method for Neutron Beam Spectral Characterization

International Nuclear Information System (INIS)

David W. Freeman

2000-01-01

A revolutionary new concept for solving the neutron spectrum unfolding problem using genetic algorithms (GAs) has recently been introduced. GAs are part of a new field of evolutionary solution techniques that mimic living systems with computer-simulated chromosome solutions that mate, mutate, and evolve to create improved solutions. The original motivation for the research was to improve spectral characterization of neutron beams associated with boron neutron capture therapy (BNCT). The GA unfolding technique has been successfully applied to problems with moderate energy resolution (up to 47 energy groups). Initial research indicates that the GA unfolding technique may well be superior to popular unfolding methods in common use. Research now under way at Kansas State University is focused on optimizing the unfolding algorithm and expanding its energy resolution to unfold detailed beam spectra based on multiple foil measurements. Indications are that the final code will significantly outperform current, state-of-the-art codes in use by the scientific community

Wavelet Filter Banks for Super-Resolution SAR Imaging

Science.gov (United States)

Sheybani, Ehsan O.; Deshpande, Manohar; Memarsadeghi, Nargess

2011-01-01

This paper discusses Innovative wavelet-based filter banks designed to enhance the analysis of super resolution Synthetic Aperture Radar (SAR) images using parametric spectral methods and signal classification algorithms, SAR finds applications In many of NASA's earth science fields such as deformation, ecosystem structure, and dynamics of Ice, snow and cold land processes, and surface water and ocean topography. Traditionally, standard methods such as Fast-Fourier Transform (FFT) and Inverse Fast-Fourier Transform (IFFT) have been used to extract Images from SAR radar data, Due to non-parametric features of these methods and their resolution limitations and observation time dependence, use of spectral estimation and signal pre- and post-processing techniques based on wavelets to process SAR radar data has been proposed. Multi-resolution wavelet transforms and advanced spectral estimation techniques have proven to offer efficient solutions to this problem.

Science with High Spatial Resolution Far-Infrared Data

Science.gov (United States)

Terebey, Susan (Editor); Mazzarella, Joseph M. (Editor)

1994-01-01

The goal of this workshop was to discuss new science and techniques relevant to high spatial resolution processing of far-infrared data, with particular focus on high resolution processing of IRAS data. Users of the maximum correlation method, maximum entropy, and other resolution enhancement algorithms applicable to far-infrared data gathered at the Infrared Processing and Analysis Center (IPAC) for two days in June 1993 to compare techniques and discuss new results. During a special session on the third day, interested astronomers were introduced to IRAS HIRES processing, which is IPAC's implementation of the maximum correlation method to the IRAS data. Topics discussed during the workshop included: (1) image reconstruction; (2) random noise; (3) imagery; (4) interacting galaxies; (5) spiral galaxies; (6) galactic dust and elliptical galaxies; (7) star formation in Seyfert galaxies; (8) wavelet analysis; and (9) supernova remnants.

Sparsity-Based Pixel Super Resolution for Lens-Free Digital In-line Holography.

Science.gov (United States)

Song, Jun; Leon Swisher, Christine; Im, Hyungsoon; Jeong, Sangmoo; Pathania, Divya; Iwamoto, Yoshiko; Pivovarov, Misha; Weissleder, Ralph; Lee, Hakho

2016-04-21

Lens-free digital in-line holography (LDIH) is a promising technology for portable, wide field-of-view imaging. Its resolution, however, is limited by the inherent pixel size of an imaging device. Here we present a new computational approach to achieve sub-pixel resolution for LDIH. The developed method is a sparsity-based reconstruction with the capability to handle the non-linear nature of LDIH. We systematically characterized the algorithm through simulation and LDIH imaging studies. The method achieved the spatial resolution down to one-third of the pixel size, while requiring only single-frame imaging without any hardware modifications. This new approach can be used as a general framework to enhance the resolution in nonlinear holographic systems.

A three-dimensional reconstruction algorithm for an inverse-geometry volumetric CT system

International Nuclear Information System (INIS)

Schmidt, Taly Gilat; Fahrig, Rebecca; Pelc, Norbert J.

2005-01-01

An inverse-geometry volumetric computed tomography (IGCT) system has been proposed capable of rapidly acquiring sufficient data to reconstruct a thick volume in one circular scan. The system uses a large-area scanned source opposite a smaller detector. The source and detector have the same extent in the axial, or slice, direction, thus providing sufficient volumetric sampling and avoiding cone-beam artifacts. This paper describes a reconstruction algorithm for the IGCT system. The algorithm first rebins the acquired data into two-dimensional (2D) parallel-ray projections at multiple tilt and azimuthal angles, followed by a 3D filtered backprojection. The rebinning step is performed by gridding the data onto a Cartesian grid in a 4D projection space. We present a new method for correcting the gridding error caused by the finite and asymmetric sampling in the neighborhood of each output grid point in the projection space. The reconstruction algorithm was implemented and tested on simulated IGCT data. Results show that the gridding correction reduces the gridding errors to below one Hounsfield unit. With this correction, the reconstruction algorithm does not introduce significant artifacts or blurring when compared to images reconstructed from simulated 2D parallel-ray projections. We also present an investigation of the noise behavior of the method which verifies that the proposed reconstruction algorithm utilizes cross-plane rays as efficiently as in-plane rays and can provide noise comparable to an in-plane parallel-ray geometry for the same number of photons. Simulations of a resolution test pattern and the modulation transfer function demonstrate that the IGCT system, using the proposed algorithm, is capable of 0.4 mm isotropic resolution. The successful implementation of the reconstruction algorithm is an important step in establishing feasibility of the IGCT system

Edge Detection from High Resolution Remote Sensing Images using Two-Dimensional log Gabor Filter in Frequency Domain

International Nuclear Information System (INIS)

Wang, K; Yu, T; Meng, Q Y; Wang, G K; Li, S P; Liu, S H

2014-01-01

Edges are vital features to describe the structural information of images, especially high spatial resolution remote sensing images. Edge features can be used to define the boundaries between different ground objects in high spatial resolution remote sensing images. Thus edge detection is important in the remote sensing image processing. Even though many different edge detection algorithms have been proposed, it is difficult to extract the edge features from high spatial resolution remote sensing image including complex ground objects. This paper introduces a novel method to detect edges from the high spatial resolution remote sensing image based on frequency domain. Firstly, the high spatial resolution remote sensing images are Fourier transformed to obtain the magnitude spectrum image (frequency image) by FFT. Then, the frequency spectrum is analyzed by using the radius and angle sampling. Finally, two-dimensional log Gabor filter with optimal parameters is designed according to the result of spectrum analysis. Finally, dot product between the result of Fourier transform and the log Gabor filter is inverse Fourier transformed to obtain the detections. The experimental result shows that the proposed algorithm can detect edge features from the high resolution remote sensing image commendably

Refinement procedure for the image alignment in high-resolution electron tomography.

Science.gov (United States)

Houben, L; Bar Sadan, M

2011-01-01

High-resolution electron tomography from a tilt series of transmission electron microscopy images requires an accurate image alignment procedure in order to maximise the resolution of the tomogram. This is the case in particular for ultra-high resolution where even very small misalignments between individual images can dramatically reduce the fidelity of the resultant reconstruction. A tomographic-reconstruction based and marker-free method is proposed, which uses an iterative optimisation of the tomogram resolution. The method utilises a search algorithm that maximises the contrast in tomogram sub-volumes. Unlike conventional cross-correlation analysis it provides the required correlation over a large tilt angle separation and guarantees a consistent alignment of images for the full range of object tilt angles. An assessment based on experimental reconstructions shows that the marker-free procedure is competitive to the reference of marker-based procedures at lower resolution and yields sub-pixel accuracy even for simulated high-resolution data. Copyright © 2011 Elsevier B.V. All rights reserved.

CEST ANALYSIS: AUTOMATED CHANGE DETECTION FROM VERY-HIGH-RESOLUTION REMOTE SENSING IMAGES

Directory of Open Access Journals (Sweden)

M. Ehlers

2012-08-01

Full Text Available A fast detection, visualization and assessment of change in areas of crisis or catastrophes are important requirements for coordination and planning of help. Through the availability of new satellites and/or airborne sensors with very high spatial resolutions (e.g., WorldView, GeoEye new remote sensing data are available for a better detection, delineation and visualization of change. For automated change detection, a large number of algorithms has been proposed and developed. From previous studies, however, it is evident that to-date no single algorithm has the potential for being a reliable change detector for all possible scenarios. This paper introduces the Combined Edge Segment Texture (CEST analysis, a decision-tree based cooperative suite of algorithms for automated change detection that is especially designed for the generation of new satellites with very high spatial resolution. The method incorporates frequency based filtering, texture analysis, and image segmentation techniques. For the frequency analysis, different band pass filters can be applied to identify the relevant frequency information for change detection. After transforming the multitemporal images via a fast Fourier transform (FFT and applying the most suitable band pass filter, different methods are available to extract changed structures: differencing and correlation in the frequency domain and correlation and edge detection in the spatial domain. Best results are obtained using edge extraction. For the texture analysis, different 'Haralick' parameters can be calculated (e.g., energy, correlation, contrast, inverse distance moment with 'energy' so far providing the most accurate results. These algorithms are combined with a prior segmentation of the image data as well as with morphological operations for a final binary change result. A rule-based combination (CEST of the change algorithms is applied to calculate the probability of change for a particular location. CEST

Fourier Deconvolution Methods for Resolution Enhancement in Continuous-Wave EPR Spectroscopy.

Science.gov (United States)

Reed, George H; Poyner, Russell R

2015-01-01

An overview of resolution enhancement of conventional, field-swept, continuous-wave electron paramagnetic resonance spectra using Fourier transform-based deconvolution methods is presented. Basic steps that are involved in resolution enhancement of calculated spectra using an implementation based on complex discrete Fourier transform algorithms are illustrated. Advantages and limitations of the method are discussed. An application to an experimentally obtained spectrum is provided to illustrate the power of the method for resolving overlapped transitions. © 2015 Elsevier Inc. All rights reserved.

A cloud mask methodology for high resolution remote sensing data combining information from high and medium resolution optical sensors

Science.gov (United States)

Sedano, Fernando; Kempeneers, Pieter; Strobl, Peter; Kucera, Jan; Vogt, Peter; Seebach, Lucia; San-Miguel-Ayanz, Jesús

2011-09-01

This study presents a novel cloud masking approach for high resolution remote sensing images in the context of land cover mapping. As an advantage to traditional methods, the approach does not rely on thermal bands and it is applicable to images from most high resolution earth observation remote sensing sensors. The methodology couples pixel-based seed identification and object-based region growing. The seed identification stage relies on pixel value comparison between high resolution images and cloud free composites at lower spatial resolution from almost simultaneously acquired dates. The methodology was tested taking SPOT4-HRVIR, SPOT5-HRG and IRS-LISS III as high resolution images and cloud free MODIS composites as reference images. The selected scenes included a wide range of cloud types and surface features. The resulting cloud masks were evaluated through visual comparison. They were also compared with ad-hoc independently generated cloud masks and with the automatic cloud cover assessment algorithm (ACCA). In general the results showed an agreement in detected clouds higher than 95% for clouds larger than 50 ha. The approach produced consistent results identifying and mapping clouds of different type and size over various land surfaces including natural vegetation, agriculture land, built-up areas, water bodies and snow.

Spatial scales of pollution from variable resolution satellite imaging.

Science.gov (United States)

Chudnovsky, Alexandra A; Kostinski, Alex; Lyapustin, Alexei; Koutrakis, Petros

2013-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not adequate for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM(2.5) as measured by the EPA ground monitoring stations was investigated at varying spatial scales. Our analysis suggested that the correlation between PM(2.5) and AOD decreased significantly as AOD resolution was degraded. This is so despite the intrinsic mismatch between PM(2.5) ground level measurements and AOD vertically integrated measurements. Furthermore, the fine resolution results indicated spatial variability in particle concentration at a sub-10 km scale. Finally, this spatial variability of AOD within the urban domain was shown to depend on PM(2.5) levels and wind speed. Copyright © 2012 Elsevier Ltd. All rights reserved.

Assessment of two aerosol optical thickness retrieval algorithms applied to MODIS Aqua and Terra measurements in Europe

Directory of Open Access Journals (Sweden)

P. Glantz

2012-07-01

Full Text Available The aim of the present study is to validate AOT (aerosol optical thickness and Ångström exponent (α, obtained from MODIS (MODerate resolution Imaging Spectroradiometer Aqua and Terra calibrated level 1 data (1 km horizontal resolution at ground with the SAER (Satellite AErosol Retrieval algorithm and with MODIS Collection 5 (c005 standard product retrievals (10 km horizontal resolution, against AERONET (AErosol RObotic NETwork sun photometer observations over land surfaces in Europe. An inter-comparison of AOT at 0.469 nm obtained with the two algorithms has also been performed. The time periods investigated were chosen to enable a validation of the findings of the two algorithms for a maximal possible variation in sun elevation. The satellite retrievals were also performed with a significant variation in the satellite-viewing geometry, since Aqua and Terra passed the investigation area twice a day for several of the cases analyzed. The validation with AERONET shows that the AOT at 0.469 and 0.555 nm obtained with MODIS c005 is within the expected uncertainty of one standard deviation of the MODIS c005 retrievals (ΔAOT = ± 0.05 ± 0.15 · AOT. The AOT at 0.443 nm retrieved with SAER, but with a much finer spatial resolution, also agreed reasonably well with AERONET measurements. The majority of the SAER AOT values are within the MODIS c005 expected uncertainty range, although somewhat larger average absolute deviation occurs compared to the results obtained with the MODIS c005 algorithm. The discrepancy between AOT from SAER and AERONET is, however, substantially larger for the wavelength 488 nm. This means that the values are, to a larger extent, outside of the expected MODIS uncertainty range. In addition, both satellite retrieval algorithms are unable to estimate α accurately, although the MODIS c005 algorithm performs better. Based on the inter-comparison of the SAER and MODIS c005 algorithms, it was found that SAER on the whole is

Large-scale runoff generation – parsimonious parameterisation using high-resolution topography

Directory of Open Access Journals (Sweden)

L. Gong

2011-08-01

Full Text Available World water resources have primarily been analysed by global-scale hydrological models in the last decades. Runoff generation in many of these models are based on process formulations developed at catchments scales. The division between slow runoff (baseflow and fast runoff is primarily governed by slope and spatial distribution of effective water storage capacity, both acting at very small scales. Many hydrological models, e.g. VIC, account for the spatial storage variability in terms of statistical distributions; such models are generally proven to perform well. The statistical approaches, however, use the same runoff-generation parameters everywhere in a basin. The TOPMODEL concept, on the other hand, links the effective maximum storage capacity with real-world topography. Recent availability of global high-quality, high-resolution topographic data makes TOPMODEL attractive as a basis for a physically-based runoff-generation algorithm at large scales, even if its assumptions are not valid in flat terrain or for deep groundwater systems. We present a new runoff-generation algorithm for large-scale hydrology based on TOPMODEL concepts intended to overcome these problems. The TRG (topography-derived runoff generation algorithm relaxes the TOPMODEL equilibrium assumption so baseflow generation is not tied to topography. TRG only uses the topographic index to distribute average storage to each topographic index class. The maximum storage capacity is proportional to the range of topographic index and is scaled by one parameter. The distribution of storage capacity within large-scale grid cells is obtained numerically through topographic analysis. The new topography-derived distribution function is then inserted into a runoff-generation framework similar VIC's. Different basin parts are parameterised by different storage capacities, and different shapes of the storage-distribution curves depend on their topographic characteristics. The TRG algorithm

Cubic scaling algorithms for RPA correlation using interpolative separable density fitting

Science.gov (United States)

Lu, Jianfeng; Thicke, Kyle

2017-12-01

We present a new cubic scaling algorithm for the calculation of the RPA correlation energy. Our scheme splits up the dependence between the occupied and virtual orbitals in χ0 by use of Cauchy's integral formula. This introduces an additional integral to be carried out, for which we provide a geometrically convergent quadrature rule. Our scheme also uses the newly developed Interpolative Separable Density Fitting algorithm to further reduce the computational cost in a way analogous to that of the Resolution of Identity method.

Accuracy Improvement for Light-Emitting-Diode-Based Colorimeter by Iterative Algorithm

Science.gov (United States)

Yang, Pao-Keng

2011-09-01

We present a simple algorithm, combining an interpolating method with an iterative calculation, to enhance the resolution of spectral reflectance by removing the spectral broadening effect due to the finite bandwidth of the light-emitting diode (LED) from it. The proposed algorithm can be used to improve the accuracy of a reflective colorimeter using multicolor LEDs as probing light sources and is also applicable to the case when the probing LEDs have different bandwidths in different spectral ranges, to which the powerful deconvolution method cannot be applied.

Robust microbubble tracking for super resolution imaging in ultrasound

DEFF Research Database (Denmark)

Hansen, Kristoffer B.; Villagómez Hoyos, Carlos Armando; Brasen, Jens Christian

2016-01-01

Currently ultrasound resolution is limited by diffraction to approximately half the wavelength of the sound wave employed. In recent years, super resolution imaging techniques have overcome the diffraction limit through the localization and tracking of a sparse set of microbubbles through...... the vasculature. However, this has only been performed on fixated tissue, limiting its clinical application. This paper proposes a technique for making super resolution images on non-fixated tissue by first compensating for tissue movement and then tracking the individual microbubbles. The experiment is performed...... on the kidney of a anesthetized Sprage-Dawley rat by infusing SonoVue at 0.1× original concentration. The algorithm demonstrated in vivo that the motion compensation was capable of removing the movement caused by the mechanical ventilator. The results shows that microbubbles were localized with a higher...

A Criteria Standard for Conflict Resolution: A Vision for Guaranteeing the Safety of Self-Separation in NextGen

Science.gov (United States)

Munoz, Cesar; Butler, Ricky; Narkawicz, Anthony; Maddalon, Jeffrey; Hagen, George

2010-01-01

Distributed approaches for conflict resolution rely on analyzing the behavior of each aircraft to ensure that system-wide safety properties are maintained. This paper presents the criteria method, which increases the quality and efficiency of a safety assurance analysis for distributed air traffic concepts. The criteria standard is shown to provide two key safety properties: safe separation when only one aircraft maneuvers and safe separation when both aircraft maneuver at the same time. This approach is complemented with strong guarantees of correct operation through formal verification. To show that an algorithm is correct, i.e., that it always meets its specified safety property, one must only show that the algorithm satisfies the criteria. Once this is done, then the algorithm inherits the safety properties of the criteria. An important consequence of this approach is that there is no requirement that both aircraft execute the same conflict resolution algorithm. Therefore, the criteria approach allows different avionics manufacturers or even different airlines to use different algorithms, each optimized according to their own proprietary concerns.

A new MUSIC electromagnetic imaging method with enhanced resolution for small inclusions

Energy Technology Data Exchange (ETDEWEB)

Zhong Yu; Chen Xudong [Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 117576 (Singapore)], E-mail: zhongyu@nus.edu.sg

2008-11-01

This paper investigates the influence of test dipole on the resolution of the multiple signal classification (MUSIC) imaging method applied to the electromagnetic inverse scattering problem of determining the locations of a collection of small objects embedded in a known background medium. Based on the analysis of the induced electric dipoles in eigenstates, an algorithm is proposed to determine the test dipole that generates a pseudo-spectrum with enhanced resolution. The amplitudes in three directions of the optimal test dipole are not necessarily in phase, i.e., the optimal test dipole may not correspond to a physical direction in the real three-dimensional space. In addition, the proposed test-dipole-searching algorithm is able to deal with some special scenarios, due to the shapes and materials of objects, to which the standard MUSIC doesn't apply.

A new MUSIC electromagnetic imaging method with enhanced resolution for small inclusions

International Nuclear Information System (INIS)

Zhong Yu; Chen Xudong

2008-01-01

This paper investigates the influence of test dipole on the resolution of the multiple signal classification (MUSIC) imaging method applied to the electromagnetic inverse scattering problem of determining the locations of a collection of small objects embedded in a known background medium. Based on the analysis of the induced electric dipoles in eigenstates, an algorithm is proposed to determine the test dipole that generates a pseudo-spectrum with enhanced resolution. The amplitudes in three directions of the optimal test dipole are not necessarily in phase, i.e., the optimal test dipole may not correspond to a physical direction in the real three-dimensional space. In addition, the proposed test-dipole-searching algorithm is able to deal with some special scenarios, due to the shapes and materials of objects, to which the standard MUSIC doesn't apply.

Precise Aperture-Dependent Motion Compensation with Frequency Domain Fast Back-Projection Algorithm

Directory of Open Access Journals (Sweden)

Man Zhang

2017-10-01

Full Text Available Precise azimuth-variant motion compensation (MOCO is an essential and difficult task for high-resolution synthetic aperture radar (SAR imagery. In conventional post-filtering approaches, residual azimuth-variant motion errors are generally compensated through a set of spatial post-filters, where the coarse-focused image is segmented into overlapped blocks concerning the azimuth-dependent residual errors. However, image domain post-filtering approaches, such as precise topography- and aperture-dependent motion compensation algorithm (PTA, have difficulty of robustness in declining, when strong motion errors are involved in the coarse-focused image. In this case, in order to capture the complete motion blurring function within each image block, both the block size and the overlapped part need necessary extension leading to degeneration of efficiency and robustness inevitably. Herein, a frequency domain fast back-projection algorithm (FDFBPA is introduced to deal with strong azimuth-variant motion errors. FDFBPA disposes of the azimuth-variant motion errors based on a precise azimuth spectrum expression in the azimuth wavenumber domain. First, a wavenumber domain sub-aperture processing strategy is introduced to accelerate computation. After that, the azimuth wavenumber spectrum is partitioned into a set of wavenumber blocks, and each block is formed into a sub-aperture coarse resolution image via the back-projection integral. Then, the sub-aperture images are straightforwardly fused together in azimuth wavenumber domain to obtain a full resolution image. Moreover, chirp-Z transform (CZT is also introduced to implement the sub-aperture back-projection integral, increasing the efficiency of the algorithm. By disusing the image domain post-filtering strategy, robustness of the proposed algorithm is improved. Both simulation and real-measured data experiments demonstrate the effectiveness and superiority of the proposal.

Evaluation of PET Imaging Resolution Using 350 mu{m} Pixelated CZT as a VP-PET Insert Detector

Science.gov (United States)

Yin, Yongzhi; Chen, Ximeng; Li, Chongzheng; Wu, Heyu; Komarov, Sergey; Guo, Qingzhen; Krawczynski, Henric; Meng, Ling-Jian; Tai, Yuan-Chuan

2014-02-01

A cadmium-zinc-telluride (CZT) detector with 350 μm pitch pixels was studied in high-resolution positron emission tomography (PET) imaging applications. The PET imaging system was based on coincidence detection between a CZT detector and a lutetium oxyorthosilicate (LSO)-based Inveon PET detector in virtual-pinhole PET geometry. The LSO detector is a 20 ×20 array, with 1.6 mm pitches, and 10 mm thickness. The CZT detector uses ac 20 ×20 ×5 mm substrate, with 350 μm pitch pixelated anodes and a coplanar cathode. A NEMA NU4 Na-22 point source of 250 μm in diameter was imaged by this system. Experiments show that the image resolution of single-pixel photopeak events was 590 μm FWHM while the image resolution of double-pixel photopeak events was 640 μm FWHM. The inclusion of double-pixel full-energy events increased the sensitivity of the imaging system. To validate the imaging experiment, we conducted a Monte Carlo (MC) simulation for the same PET system in Geant4 Application for Emission Tomography. We defined LSO detectors as a scanner ring and 350 μm pixelated CZT detectors as an insert ring. GATE simulated coincidence data were sorted into an insert-scanner sinogram and reconstructed. The image resolution of MC-simulated data (which did not factor in positron range and acolinearity effect) was 460 μm at FWHM for single-pixel events. The image resolutions of experimental data, MC simulated data, and theoretical calculation are all close to 500 μm FWHM when the proposed 350 μm pixelated CZT detector is used as a PET insert. The interpolation algorithm for the charge sharing events was also investigated. The PET image that was reconstructed using the interpolation algorithm shows improved image resolution compared with the image resolution without interpolation algorithm.

Effect of ADS-B Characteristics on Airborne Conflict Detection and Resolution

NARCIS (Netherlands)

Langejan, T.P.; Sunil, E.; Ellerbroek, J.; Hoekstra, J.M.

2016-01-01

Most Free-Flight concepts rely on self-separation by means of airborne Conflict Detection and Resolution (CD&R) algorithms. A key enabling technology for airborne CD&R is the Automatic Dependent Surveillance-Broadcast (ADS-B) system, which is used for direct state information exchange

Sensitivity Analysis of the Scattering-Based SARBM3D Despeckling Algorithm.

Science.gov (United States)

Di Simone, Alessio

2016-06-25

Synthetic Aperture Radar (SAR) imagery greatly suffers from multiplicative speckle noise, typical of coherent image acquisition sensors, such as SAR systems. Therefore, a proper and accurate despeckling preprocessing step is almost mandatory to aid the interpretation and processing of SAR data by human users and computer algorithms, respectively. Very recently, a scattering-oriented version of the popular SAR Block-Matching 3D (SARBM3D) despeckling filter, named Scattering-Based (SB)-SARBM3D, was proposed. The new filter is based on the a priori knowledge of the local topography of the scene. In this paper, an experimental sensitivity analysis of the above-mentioned despeckling algorithm is carried out, and the main results are shown and discussed. In particular, the role of both electromagnetic and geometrical parameters of the surface and the impact of its scattering behavior are investigated. Furthermore, a comprehensive sensitivity analysis of the SB-SARBM3D filter against the Digital Elevation Model (DEM) resolution and the SAR image-DEM coregistration step is also provided. The sensitivity analysis shows a significant robustness of the algorithm against most of the surface parameters, while the DEM resolution plays a key role in the despeckling process. Furthermore, the SB-SARBM3D algorithm outperforms the original SARBM3D in the presence of the most realistic scattering behaviors of the surface. An actual scenario is also presented to assess the DEM role in real-life conditions.

A Solution Generator Algorithm for Decision Making based Automated Negotiation in the Construction Domain

Directory of Open Access Journals (Sweden)

Arazi Idrus

2017-12-01

Full Text Available In this paper, we present our work-in-progress of a proposed framework for automated negotiation in the construction domain. The proposed framework enables software agents to conduct negotiations and autonomously make value-based decisions. The framework consists of three main components which are, solution generator algorithm, negotiation algorithm, and conflict resolution algorithm. This paper extends the discussion on the solution generator algorithm that enables software agents to generate solutions and rank them from 1st to nth solution for the negotiation stage of the operation. The solution generator algorithm consists of three steps which are, review solutions, rank solutions, and form ranked solutions. For validation purpose, we present a scenario that utilizes the proposed algorithm to rank solutions. The validation shows that the algorithm is promising, however, it also highlights the conflict between different parties that needs further negotiation action.

TSaT-MUSIC: a novel algorithm for rapid and accurate ultrasonic 3D localization

Science.gov (United States)

Mizutani, Kyohei; Ito, Toshio; Sugimoto, Masanori; Hashizume, Hiromichi

2011-12-01

We describe a fast and accurate indoor localization technique using the multiple signal classification (MUSIC) algorithm. The MUSIC algorithm is known as a high-resolution method for estimating directions of arrival (DOAs) or propagation delays. A critical problem in using the MUSIC algorithm for localization is its computational complexity. Therefore, we devised a novel algorithm called Time Space additional Temporal-MUSIC, which can rapidly and simultaneously identify DOAs and delays of mul-ticarrier ultrasonic waves from transmitters. Computer simulations have proved that the computation time of the proposed algorithm is almost constant in spite of increasing numbers of incoming waves and is faster than that of existing methods based on the MUSIC algorithm. The robustness of the proposed algorithm is discussed through simulations. Experiments in real environments showed that the standard deviation of position estimations in 3D space is less than 10 mm, which is satisfactory for indoor localization.

Development of Signal Processing Algorithms for High Resolution Airborne Millimeter Wave FMCW SAR

NARCIS (Netherlands)

Meta, A.; Hoogeboom, P.

2005-01-01

For airborne earth observation applications, there is a special interest in lightweight, cost effective, imaging sensors of high resolution. The combination of Frequency Modulated Continuous Wave (FMCW) technology and Synthetic Aperture Radar (SAR) techniques can lead to such a sensor. In this

Upwind algorithm for the parabolized Navier-Stokes equations

Science.gov (United States)

Lawrence, Scott L.; Tannehill, John C.; Chausee, Denny S.

1989-01-01

A new upwind algorithm based on Roe's scheme has been developed to solve the two-dimensional parabolized Navier-Stokes equations. This method does not require the addition of user-specified smoothing terms for the capture of discontinuities such as shock waves. Thus, the method is easy to use and can be applied without modification to a wide variety of supersonic flowfields. The advantages and disadvantages of this adaptation are discussed in relation to those of the conventional Beam-Warming (1978) scheme in terms of accuracy, stability, computer time and storage requirements, and programming effort. The new algorithm has been validated by applying it to three laminar test cases, including flat-plate boundary-layer flow, hypersonic flow past a 15-deg compression corner, and hypersonic flow into a converging inlet. The computed results compare well with experiment and show a dramatic improvement in the resolution of flowfield details when compared with results obtained using the conventional Beam-Warming algorithm.

Resolution dependence on phase extraction by the Hilbert transform in phase calibrated and dispersion compensated ultrahigh resolution spectrometer-based OCT

DEFF Research Database (Denmark)

Israelsen, Niels Møller; Maria, Michael; Feuchter, Thomas

2018-01-01

-linearities lead together to an unknown chirp of the detected interferogram. One method to compensate for the chirp is to perform a pixel-wavenumber calibration versus phase that requires numerical extraction of the phase. Typically a Hilbert transform algorithm is employed to extract the optical phase versus...... wavenumber for calibration and dispersion compensation. In this work we demonstrate UHR-OCT at 1300 nm using a Super continuum source and highlight the resolution constraints in using the Hilbert transform algorithm when extracting the optical phase for calibration and dispersion compensation. We demonstrate...... that the constraints cannot be explained purely by the numerical errors in the data processing module utilizing the Hilbert transform but must be dictated by broadening mechanisms originating from the experimentally obtained interferograms....

PolyPole-1: An accurate numerical algorithm for intra-granular fission gas release

International Nuclear Information System (INIS)

Pizzocri, D.; Rabiti, C.; Luzzi, L.; Barani, T.; Van Uffelen, P.; Pastore, G.

2016-01-01

The transport of fission gas from within the fuel grains to the grain boundaries (intra-granular fission gas release) is a fundamental controlling mechanism of fission gas release and gaseous swelling in nuclear fuel. Hence, accurate numerical solution of the corresponding mathematical problem needs to be included in fission gas behaviour models used in fuel performance codes. Under the assumption of equilibrium between trapping and resolution, the process can be described mathematically by a single diffusion equation for the gas atom concentration in a grain. In this paper, we propose a new numerical algorithm (PolyPole-1) to efficiently solve the fission gas diffusion equation in time-varying conditions. The PolyPole-1 algorithm is based on the analytic modal solution of the diffusion equation for constant conditions, combined with polynomial corrective terms that embody the information on the deviation from constant conditions. The new algorithm is verified by comparing the results to a finite difference solution over a large number of randomly generated operation histories. Furthermore, comparison to state-of-the-art algorithms used in fuel performance codes demonstrates that the accuracy of PolyPole-1 is superior to other algorithms, with similar computational effort. Finally, the concept of PolyPole-1 may be extended to the solution of the general problem of intra-granular fission gas diffusion during non-equilibrium trapping and resolution, which will be the subject of future work. - Highlights: • A new numerical algorithm (PolyPole-1) for intra-granular fission gas release in time-varying conditions is developed. • The concept combines the modal analytic solution for constant conditions and a polynomial correction. • PolyPole-1 is extensively verified and compared to other state-of-the-art algorithms. • PolyPole-1 exhibits a superior accuracy and a similar computational time relative to other algorithms. • The PolyPole-1 algorithm can be

PolyPole-1: An accurate numerical algorithm for intra-granular fission gas release

Energy Technology Data Exchange (ETDEWEB)

Pizzocri, D. [Politecnico di Milano, Department of Energy, Nuclear Engineering Division, Via La Masa 34, 20156 Milano (Italy); Rabiti, C. [Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-3840 (United States); Luzzi, L.; Barani, T. [Politecnico di Milano, Department of Energy, Nuclear Engineering Division, Via La Masa 34, 20156 Milano (Italy); Van Uffelen, P. [European Commission, Joint Research Centre, Institute for Transuranium Elements, P.O. Box 2340, 76125 Karlsruhe (Germany); Pastore, G., E-mail: giovanni.pastore@inl.gov [Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-3840 (United States)

2016-09-15

The transport of fission gas from within the fuel grains to the grain boundaries (intra-granular fission gas release) is a fundamental controlling mechanism of fission gas release and gaseous swelling in nuclear fuel. Hence, accurate numerical solution of the corresponding mathematical problem needs to be included in fission gas behaviour models used in fuel performance codes. Under the assumption of equilibrium between trapping and resolution, the process can be described mathematically by a single diffusion equation for the gas atom concentration in a grain. In this paper, we propose a new numerical algorithm (PolyPole-1) to efficiently solve the fission gas diffusion equation in time-varying conditions. The PolyPole-1 algorithm is based on the analytic modal solution of the diffusion equation for constant conditions, combined with polynomial corrective terms that embody the information on the deviation from constant conditions. The new algorithm is verified by comparing the results to a finite difference solution over a large number of randomly generated operation histories. Furthermore, comparison to state-of-the-art algorithms used in fuel performance codes demonstrates that the accuracy of PolyPole-1 is superior to other algorithms, with similar computational effort. Finally, the concept of PolyPole-1 may be extended to the solution of the general problem of intra-granular fission gas diffusion during non-equilibrium trapping and resolution, which will be the subject of future work. - Highlights: • A new numerical algorithm (PolyPole-1) for intra-granular fission gas release in time-varying conditions is developed. • The concept combines the modal analytic solution for constant conditions and a polynomial correction. • PolyPole-1 is extensively verified and compared to other state-of-the-art algorithms. • PolyPole-1 exhibits a superior accuracy and a similar computational time relative to other algorithms. • The PolyPole-1 algorithm can be

Switching algorithm for maglev train double-modular redundant positioning sensors.

Science.gov (United States)

He, Ning; Long, Zhiqiang; Xue, Song

2012-01-01

High-resolution positioning for maglev trains is implemented by detecting the tooth-slot structure of the long stator installed along the rail, but there are large joint gaps between long stator sections. When a positioning sensor is below a large joint gap, its positioning signal is invalidated, thus double-modular redundant positioning sensors are introduced into the system. This paper studies switching algorithms for these redundant positioning sensors. At first, adaptive prediction is applied to the sensor signals. The prediction errors are used to trigger sensor switching. In order to enhance the reliability of the switching algorithm, wavelet analysis is introduced to suppress measuring disturbances without weakening the signal characteristics reflecting the stator joint gap based on the correlation between the wavelet coefficients of adjacent scales. The time delay characteristics of the method are analyzed to guide the algorithm simplification. Finally, the effectiveness of the simplified switching algorithm is verified through experiments.

Switching Algorithm for Maglev Train Double-Modular Redundant Positioning Sensors

Directory of Open Access Journals (Sweden)

Song Xue

2012-08-01

Full Text Available High-resolution positioning for maglev trains is implemented by detecting the tooth-slot structure of the long stator installed along the rail, but there are large joint gaps between long stator sections. When a positioning sensor is below a large joint gap, its positioning signal is invalidated, thus double-modular redundant positioning sensors are introduced into the system. This paper studies switching algorithms for these redundant positioning sensors. At first, adaptive prediction is applied to the sensor signals. The prediction errors are used to trigger sensor switching. In order to enhance the reliability of the switching algorithm, wavelet analysis is introduced to suppress measuring disturbances without weakening the signal characteristics reflecting the stator joint gap based on the correlation between the wavelet coefficients of adjacent scales. The time delay characteristics of the method are analyzed to guide the algorithm simplification. Finally, the effectiveness of the simplified switching algorithm is verified through experiments.

TRIB3 protein denotes a good prognosis in breast cancer patients and is associated with hypoxia sensitivity

International Nuclear Information System (INIS)

Wennemers, Marloes; Bussink, Johan; Grebenchtchikov, Nicolai; Sweep, Fred C.G.J.; Span, Paul N.

2011-01-01

Background: Tribbles homolog 3 (TRIB3) is a pseudokinase involved in the regulation of several signaling pathways involved in cell survival and/or cell stress. Here, we determined the correlation between breast cancer prognosis and TRIB3 protein levels and established the role of TRIB3 in cell survival after hypoxia and/or radiotherapy. Material and methods: TRIB3 mRNA and protein were quantified in a new independent breast cancer patient cohort using QPCR and a new specific avian antibody against TRIB3. In addition, we used siRNA-mediated knockdown of TRIB3 in a colony-forming assay after hypoxia and radiotherapy. Results: TRIB3 mRNA and protein levels did not correlate in breast cancer cell lines or human breast cancer material. We validated our earlier finding that high TRIB3 mRNA denotes a poor prognosis, but found that high TRIB3 protein levels were associated with a good prognosis in breast cancer patients. We also show that knockdown of TRIB3 resulted in an increased survival under hypoxic conditions. Conclusion: Whereas mRNA levels of TRIB3 are related with a poor prognosis, TRIB3 protein is associated with a good prognosis in human breast cancer patients, possibly due to the fact that TRIB3 is involved in hypoxia tolerance.

Pinhole SPECT: high resolution imaging of brain tumours in small laboratory animals

International Nuclear Information System (INIS)

Franceschim, M.; Bokulic, T.; Kusic, Z.; Strand, S.E.; Erlandsson, K.

1994-01-01

The performance properties of pinhole SPECT and the application of this technology to evaluate radionuclide uptake in brain in small laboratory animals were investigated. System sensitivity and spatial resolution measurements of a rotating scintillation camera system were made for a low energy pinhole collimator equipped with 2.0 mm aperture pinhole insert. Projection data were acquired at 4 degree increments over 360 degrees in the step and shoot mode using a 4.5 cm radius of rotation. Pinhole planar and SPECT imaging were obtained to evaluate regional uptake of Tl-201, Tc-99m-MIBI, Tc-99m-HMPAO and Tc-99m-DTPA in tumor and control regions of the brain in a primary brain tumor model in Fisher 344 rats. Pinhole SPECT images were reconstructed using a modified cone- beam algorithm developed from a two dimensional fan-beam filtered backprojection algorithm. The reconstructed transaxial resolution of 2.8 FWHM and system sensitivity of 0.086 c/s/kBq with the 2.0 mm pinhole collimator aperture were measured. Tumor to non-tumor uptake ratios at 19-28 days post tumor cell inoculation varied by a factor > 20:1 on SPECT images. Pinhole SPECT provides an important new approach for performing high resolution imaging: the resolution properties of pinhole SPECT are superior to those which have been achieved with conventional SPECT or PET imaging technologies. (author)

Improved k-t PCA Algorithm Using Artificial Sparsity in Dynamic MRI.

Science.gov (United States)

Wang, Yiran; Chen, Zhifeng; Wang, Jing; Yuan, Lixia; Xia, Ling; Liu, Feng

2017-01-01

The k - t principal component analysis ( k - t PCA) is an effective approach for high spatiotemporal resolution dynamic magnetic resonance (MR) imaging. However, it suffers from larger residual aliasing artifacts and noise amplification when the reduction factor goes higher. To further enhance the performance of this technique, we propose a new method called sparse k - t PCA that combines the k - t PCA algorithm with an artificial sparsity constraint. It is a self-calibrated procedure that is based on the traditional k - t PCA method by further eliminating the reconstruction error derived from complex subtraction of the sampled k - t space from the original reconstructed k - t space. The proposed method is tested through both simulations and in vivo datasets with different reduction factors. Compared to the standard k - t PCA algorithm, the sparse k - t PCA can improve the normalized root-mean-square error performance and the accuracy of temporal resolution. It is thus useful for rapid dynamic MR imaging.

Study on characteristic points of boiling curve by using wavelet analysis and genetic algorithm

International Nuclear Information System (INIS)

Wei Huiming; Su Guanghui; Qiu Suizheng; Yang Xingbo

2009-01-01

Based on the wavelet analysis theory of signal singularity detection,the critical heat flux (CHF) and minimum film boiling starting point (q min ) of boiling curves can be detected and analyzed by using the wavelet multi-resolution analysis. To predict the CHF in engineering, empirical relations were obtained based on genetic algorithm. The results of wavelet detection and genetic algorithm prediction are consistent with experimental data very well. (authors)

Hybrid sparse blind deconvolution: an implementation of SOOT algorithm to real data

Science.gov (United States)

Pakmanesh, Parvaneh; Goudarzi, Alireza; Kourki, Meisam

2018-06-01

Getting information of seismic data depends on deconvolution as an important processing step; it provides the reflectivity series by signal compression. This compression can be obtained by removing the wavelet effects on the traces. The recently blind deconvolution has provided reliable performance for sparse signal recovery. In this study, two deconvolution methods have been implemented to the seismic data; the convolution of these methods provides a robust spiking deconvolution approach. This hybrid deconvolution is applied using the sparse deconvolution (MM algorithm) and the Smoothed-One-Over-Two algorithm (SOOT) in a chain. The MM algorithm is based on the minimization of the cost function defined by standards l1 and l2. After applying the two algorithms to the seismic data, the SOOT algorithm provided well-compressed data with a higher resolution than the MM algorithm. The SOOT algorithm requires initial values to be applied for real data, such as the wavelet coefficients and reflectivity series that can be achieved through the MM algorithm. The computational cost of the hybrid method is high, and it is necessary to be implemented on post-stack or pre-stack seismic data of complex structure regions.

Evaluation of 3D reconstruction algorithms for a small animal PET camera

International Nuclear Information System (INIS)

Johnson, C.A.; Gandler, W.R.; Seidel, J.

1996-01-01

The use of paired, opposing position-sensitive phototube scintillation cameras (SCs) operating in coincidence for small animal imaging with positron emitters is currently under study. Because of the low sensitivity of the system even in 3D mode and the need to produce images with high resolution, it was postulated that a 3D expectation maximization (EM) reconstruction algorithm might be well suited for this application. We investigated four reconstruction algorithms for the 3D SC PET camera: 2D filtered back-projection (FBP), 2D ordered subset EM (OSEM), 3D reprojection (3DRP), and 3D OSEM. Noise was assessed for all slices by the coefficient of variation in a simulated uniform cylinder. Resolution was assessed from a simulation of 15 point sources in the warm background of the uniform cylinder. At comparable noise levels, the resolution achieved with OSEM (0.9-mm to 1.2-mm) is significantly better than that obtained with FBP or 3DRP (1.5-mm to 2.0-mm.) Images of a rat skull labeled with 18 F-fluoride suggest that 3D OSEM can improve image quality of a small animal PET camera

Tunable output-frequency filter algorithm for imaging through scattering media under LED illumination

Science.gov (United States)

Zhou, Meiling; Singh, Alok Kumar; Pedrini, Giancarlo; Osten, Wolfgang; Min, Junwei; Yao, Baoli

2018-03-01

We present a tunable output-frequency filter (TOF) algorithm to reconstruct the object from noisy experimental data under low-power partially coherent illumination, such as LED, when imaging through scattering media. In the iterative algorithm, we employ Gaussian functions with different filter windows at different stages of iteration process to reduce corruption from experimental noise to search for a global minimum in the reconstruction. In comparison with the conventional iterative phase retrieval algorithm, we demonstrate that the proposed TOF algorithm achieves consistent and reliable reconstruction in the presence of experimental noise. Moreover, the spatial resolution and distinctive features are retained in the reconstruction since the filter is applied only to the region outside the object. The feasibility of the proposed method is proved by experimental results.

A Novel DOA Estimation Algorithm Using Array Rotation Technique

Directory of Open Access Journals (Sweden)

Xiaoyu Lan

2014-03-01

Full Text Available The performance of traditional direction of arrival (DOA estimation algorithm based on uniform circular array (UCA is constrained by the array aperture. Furthermore, the array requires more antenna elements than targets, which will increase the size and weight of the device and cause higher energy loss. In order to solve these issues, a novel low energy algorithm utilizing array base-line rotation for multiple targets estimation is proposed. By rotating two elements and setting a fixed time delay, even the number of elements is selected to form a virtual UCA. Then, the received data of signals will be sampled at multiple positions, which improves the array elements utilization greatly. 2D-DOA estimation of the rotation array is accomplished via multiple signal classification (MUSIC algorithms. Finally, the Cramer-Rao bound (CRB is derived and simulation results verified the effectiveness of the proposed algorithm with high resolution and estimation accuracy performance. Besides, because of the significant reduction of array elements number, the array antennas system is much simpler and less complex than traditional array.

High-definition computed tomography for coronary artery stents imaging: Initial evaluation of the optimal reconstruction algorithm.

Science.gov (United States)

Cui, Xiaoming; Li, Tao; Li, Xin; Zhou, Weihua

2015-05-01

The aim of this study was to evaluate the in vivo performance of four image reconstruction algorithms in a high-definition CT (HDCT) scanner with improved spatial resolution for the evaluation of coronary artery stents and intrastent lumina. Thirty-nine consecutive patients with a total of 71 implanted coronary stents underwent coronary CT angiography (CCTA) on a HDCT (Discovery CT 750 HD; GE Healthcare) with the high-resolution scanning mode. Four different reconstruction algorithms (HD-stand, HD-detail; HD-stand-plus; HD-detail-plus) were applied to reconstruct the stented coronary arteries. Image quality for stent characterization was assessed. Image noise and intrastent luminal diameter were measured. The relationship between the measurement of inner stent diameter (ISD) and the true stent diameter (TSD) and stent type were analysed. The stent-dedicated kernel (HD-detail) offered the highest percentage (53.5%) of good image quality for stent characterization and the highest ratio (68.0±8.4%) of visible stent lumen/true stent lumen for luminal diameter measurement at the expense of an increased overall image noise. The Pearson correlation coefficient between the ISD and TSD measurement and spearman correlation coefficient between the ISD measurement and stent type were 0.83 and 0.48, respectively. Compared with standard reconstruction algorithms, high-definition CT imaging technique with dedicated high-resolution reconstruction algorithm provides more accurate stent characterization and intrastent luminal diameter measurement. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Image-based point spread function implementation in a fully 3D OSEM reconstruction algorithm for PET.

Science.gov (United States)

Rapisarda, E; Bettinardi, V; Thielemans, K; Gilardi, M C

2010-07-21

The interest in positron emission tomography (PET) and particularly in hybrid integrated PET/CT systems has significantly increased in the last few years due to the improved quality of the obtained images. Nevertheless, one of the most important limits of the PET imaging technique is still its poor spatial resolution due to several physical factors originating both at the emission (e.g. positron range, photon non-collinearity) and at detection levels (e.g. scatter inside the scintillating crystals, finite dimensions of the crystals and depth of interaction). To improve the spatial resolution of the images, a possible way consists of measuring the point spread function (PSF) of the system and then accounting for it inside the reconstruction algorithm. In this work, the system response of the GE Discovery STE operating in 3D mode has been characterized by acquiring (22)Na point sources in different positions of the scanner field of view. An image-based model of the PSF was then obtained by fitting asymmetric two-dimensional Gaussians on the (22)Na images reconstructed with small pixel sizes. The PSF was then incorporated, at the image level, in a three-dimensional ordered subset maximum likelihood expectation maximization (OS-MLEM) reconstruction algorithm. A qualitative and quantitative validation of the algorithm accounting for the PSF has been performed on phantom and clinical data, showing improved spatial resolution, higher contrast and lower noise compared with the corresponding images obtained using the standard OS-MLEM algorithm.

Patient-specific quantification of image quality: An automated method for measuring spatial resolution in clinical CT images

Energy Technology Data Exchange (ETDEWEB)

Sanders, Jeremiah, E-mail: jeremiah.sanders@duke.edu [Medical Physics Graduate Program, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Clinical Imaging Physics Group, Duke University, Durham, North Carolina 27710 (United States); Hurwitz, Lynne [Department of Radiology, Duke University, Durham, North Carolina 27710 (United States); Samei, Ehsan [Medical Physics Graduate Program, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Clinical Imaging Physics Group, Duke University, Durham, North Carolina 27710 and Departments of Physics, Biomedical Engineering, Electrical and Computer Engineering, Duke University, Durham, North Carolina 27710 (United States)

2016-10-15

Purpose: To develop and validate an automated technique for evaluating the spatial resolution characteristics of clinical computed tomography (CT) images. Methods: Twenty one chest and abdominopelvic clinical CT datasets were examined in this study. An algorithm was developed to extract a CT resolution index (RI) analogous to the modulation transfer function from clinical CT images by measuring the edge-spread function (ESF) across the patient’s skin. A polygon mesh of the air-skin boundary was created. The faces of the mesh were then used to measure the ESF across the air-skin interface. The ESF was differentiated to obtain the line-spread function (LSF), and the LSF was Fourier transformed to obtain the RI. The algorithm’s ability to detect the radial dependence of the RI was investigated. RIs measured with the proposed method were compared with a conventional phantom-based method across two reconstruction algorithms (FBP and iterative) using the spatial frequency at 50% RI, f{sub 50}, as the metric for comparison. Three reconstruction kernels were investigated for each reconstruction algorithm. Finally, an observer study was conducted to determine if observers could visually perceive the differences in the measured blurriness of images reconstructed with a given reconstruction method. Results: RI measurements performed with the proposed technique exhibited the expected dependencies on the image reconstruction. The measured f{sub 50} values increased with harder kernels for both FBP and iterative reconstruction. Furthermore, the proposed algorithm was able to detect the radial dependence of the RI. Patient-specific measurements of the RI were comparable to the phantom-based technique, but the patient data exhibited a large spread in the measured f{sub 50}, indicating that some datasets were blurrier than others even when the projection data were reconstructed with the same reconstruction algorithm and kernel. Results from the observer study substantiated this

High resolution tomographic instrument development

International Nuclear Information System (INIS)

1992-01-01

Our recent work has concentrated on the development of high-resolution PET instrumentation reflecting in part the growing importance of PET in nuclear medicine imaging. We have developed a number of positron imaging instruments and have the distinction that every instrument has been placed in operation and has had an extensive history of application for basic research and clinical study. The present program is a logical continuation of these earlier successes. PCR-I, a single ring positron tomograph was the first demonstration of analog coding using BGO. It employed 4 mm detectors and is currently being used for a wide range of biological studies. These are of immense importance in guiding the direction for future instruments. In particular, PCR-II, a volume sensitive positron tomograph with 3 mm spatial resolution has benefited greatly from the studies using PCR-I. PCR-II is currently in the final stages of assembly and testing and will shortly be placed in operation for imaging phantoms, animals and ultimately humans. Perhaps the most important finding resulting from our previous study is that resolution and sensitivity must be carefully balanced to achieve a practical high resolution system. PCR-II has been designed to have the detection characteristics required to achieve 3 mm resolution in human brain under practical imaging situations. The development of algorithms by the group headed by Dr. Chesler is based on a long history of prior study including his joint work with Drs. Pelc and Reiderer and Stearns. This body of expertise will be applied to the processing of data from PCR-II when it becomes operational

High resolution tomographic instrument development

Energy Technology Data Exchange (ETDEWEB)

1992-08-01

Our recent work has concentrated on the development of high-resolution PET instrumentation reflecting in part the growing importance of PET in nuclear medicine imaging. We have developed a number of positron imaging instruments and have the distinction that every instrument has been placed in operation and has had an extensive history of application for basic research and clinical study. The present program is a logical continuation of these earlier successes. PCR-I, a single ring positron tomograph was the first demonstration of analog coding using BGO. It employed 4 mm detectors and is currently being used for a wide range of biological studies. These are of immense importance in guiding the direction for future instruments. In particular, PCR-II, a volume sensitive positron tomograph with 3 mm spatial resolution has benefited greatly from the studies using PCR-I. PCR-II is currently in the final stages of assembly and testing and will shortly be placed in operation for imaging phantoms, animals and ultimately humans. Perhaps the most important finding resulting from our previous study is that resolution and sensitivity must be carefully balanced to achieve a practical high resolution system. PCR-II has been designed to have the detection characteristics required to achieve 3 mm resolution in human brain under practical imaging situations. The development of algorithms by the group headed by Dr. Chesler is based on a long history of prior study including his joint work with Drs. Pelc and Reiderer and Stearns. This body of expertise will be applied to the processing of data from PCR-II when it becomes operational.

High resolution tomographic instrument development

Energy Technology Data Exchange (ETDEWEB)

1992-01-01

Our recent work has concentrated on the development of high-resolution PET instrumentation reflecting in part the growing importance of PET in nuclear medicine imaging. We have developed a number of positron imaging instruments and have the distinction that every instrument has been placed in operation and has had an extensive history of application for basic research and clinical study. The present program is a logical continuation of these earlier successes. PCR-I, a single ring positron tomograph was the first demonstration of analog coding using BGO. It employed 4 mm detectors and is currently being used for a wide range of biological studies. These are of immense importance in guiding the direction for future instruments. In particular, PCR-II, a volume sensitive positron tomograph with 3 mm spatial resolution has benefited greatly from the studies using PCR-I. PCR-II is currently in the final stages of assembly and testing and will shortly be placed in operation for imaging phantoms, animals and ultimately humans. Perhaps the most important finding resulting from our previous study is that resolution and sensitivity must be carefully balanced to achieve a practical high resolution system. PCR-II has been designed to have the detection characteristics required to achieve 3 mm resolution in human brain under practical imaging situations. The development of algorithms by the group headed by Dr. Chesler is based on a long history of prior study including his joint work with Drs. Pelc and Reiderer and Stearns. This body of expertise will be applied to the processing of data from PCR-II when it becomes operational.

A new approximate algorithm for image reconstruction in cone-beam spiral CT at small cone-angles

International Nuclear Information System (INIS)

Schaller, S.; Flohr, T.; Steffen, P.

1996-01-01

This paper presents a new approximate algorithm for image reconstruction with cone-beam spiral CT data at relatively small cone-angles. Based on the algorithm of Wang et al., our method combines a special complementary interpolation with filtered backprojection. The presented algorithm has three main advantages over Wang's algorithm: (1) It overcomes the pitch limitation of Wang's algorithm. (2) It significantly improves z-resolution when suitable sampling schemes are applied. (3) It avoids the waste of applied radiation dose inherent to Wang's algorithm. Usage of the total applied dose is an important requirement in medical imaging. Our method has been implemented on a standard workstation. Reconstructions of computer-simulated data of different phantoms, assuming sampling conditions and image quality requirements typical to medical CT, show encouraging results

HIGH-RESOLUTION LINEAR POLARIMETRIC IMAGING FOR THE EVENT HORIZON TELESCOPE

Energy Technology Data Exchange (ETDEWEB)

Chael, Andrew A.; Johnson, Michael D.; Narayan, Ramesh; Doeleman, Sheperd S. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Wardle, John F. C. [Brandeis University, Physics Department, Waltham, MA 02454 (United States); Bouman, Katherine L., E-mail: achael@cfa.harvard.edu [Massachusetts Institute of Technology, Computer Science and Artificial Intelligence Laboratory, 32 Vassar Street, Cambridge, MA 02139 (United States)

2016-09-20

Images of the linear polarizations of synchrotron radiation around active galactic nuclei (AGNs) highlight their projected magnetic field lines and provide key data for understanding the physics of accretion and outflow from supermassive black holes. The highest-resolution polarimetric images of AGNs are produced with Very Long Baseline Interferometry (VLBI). Because VLBI incompletely samples the Fourier transform of the source image, any image reconstruction that fills in unmeasured spatial frequencies will not be unique and reconstruction algorithms are required. In this paper, we explore some extensions of the Maximum Entropy Method (MEM) to linear polarimetric VLBI imaging. In contrast to previous work, our polarimetric MEM algorithm combines a Stokes I imager that only uses bispectrum measurements that are immune to atmospheric phase corruption, with a joint Stokes Q and U imager that operates on robust polarimetric ratios. We demonstrate the effectiveness of our technique on 7 and 3 mm wavelength quasar observations from the VLBA and simulated 1.3 mm Event Horizon Telescope observations of Sgr A* and M87. Consistent with past studies, we find that polarimetric MEM can produce superior resolution compared to the standard CLEAN algorithm, when imaging smooth and compact source distributions. As an imaging framework, MEM is highly adaptable, allowing a range of constraints on polarization structure. Polarimetric MEM is thus an attractive choice for image reconstruction with the EHT.

The semianalytical cloud retrieval algorithm for SCIAMACHY I. The validation

Directory of Open Access Journals (Sweden)

A. A. Kokhanovsky

2006-01-01

Full Text Available A recently developed cloud retrieval algorithm for the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY is briefly presented and validated using independent and well tested cloud retrieval techniques based on the look-up-table approach for MODeration resolutIon Spectrometer (MODIS data. The results of the cloud top height retrievals using measurements in the oxygen A-band by an airborne crossed Czerny-Turner spectrograph and the Global Ozone Monitoring Experiment (GOME instrument are compared with those obtained from airborne dual photography and retrievals using data from Along Track Scanning Radiometer (ATSR-2, respectively.

Image processing and resolution restoration of fast-neutron hodoscope data

International Nuclear Information System (INIS)

Rhodes, E.A.; DeVolpi, A.

1982-01-01

The fast-neutron hodoscope is a cineradiographic device that monitors fuel motion within thick opaque test capsules during radiation transients at the Transient Reactor Test Facility reactor which simulate accident conditions in power reactors. By means of a collimator and detector array, emissive neutron radiographic digital data is collected in time-resolved and static (scan) modes. Data is digitally reconstructed into raidographic images and used directly for quantitative analysis. Spatial resolution is adequate in most cases, but is marginal for a few experiments. Collimator repositioning, scan increment size-reduction, and deconvolution algorithms are being applied to improve resolution of existing collimators

Sequential unconstrained minimization algorithms for constrained optimization

International Nuclear Information System (INIS)

Byrne, Charles

2008-01-01

The problem of minimizing a function f(x):R J → R, subject to constraints on the vector variable x, occurs frequently in inverse problems. Even without constraints, finding a minimizer of f(x) may require iterative methods. We consider here a general class of iterative algorithms that find a solution to the constrained minimization problem as the limit of a sequence of vectors, each solving an unconstrained minimization problem. Our sequential unconstrained minimization algorithm (SUMMA) is an iterative procedure for constrained minimization. At the kth step we minimize the function G k (x)=f(x)+g k (x), to obtain x k . The auxiliary functions g k (x):D subset of R J → R + are nonnegative on the set D, each x k is assumed to lie within D, and the objective is to minimize the continuous function f:R J → R over x in the set C = D-bar, the closure of D. We assume that such minimizers exist, and denote one such by x-circumflex. We assume that the functions g k (x) satisfy the inequalities 0≤g k (x)≤G k-1 (x)-G k-1 (x k-1 ), for k = 2, 3, .... Using this assumption, we show that the sequence {(x k )} is decreasing and converges to f(x-circumflex). If the restriction of f(x) to D has bounded level sets, which happens if x-circumflex is unique and f(x) is closed, proper and convex, then the sequence {x k } is bounded, and f(x*)=f(x-circumflex), for any cluster point x*. Therefore, if x-circumflex is unique, x* = x-circumflex and {x k } → x-circumflex. When x-circumflex is not unique, convergence can still be obtained, in particular cases. The SUMMA includes, as particular cases, the well-known barrier- and penalty-function methods, the simultaneous multiplicative algebraic reconstruction technique (SMART), the proximal minimization algorithm of Censor and Zenios, the entropic proximal methods of Teboulle, as well as certain cases of gradient descent and the Newton–Raphson method. The proof techniques used for SUMMA can be extended to obtain related results

Sparse Variational Bayesian SAGE Algorithm With Application to the Estimation of Multipath Wireless Channels

DEFF Research Database (Denmark)

Shutin, Dmitriy; Fleury, Bernard Henri

2011-01-01

In this paper, we develop a sparse variational Bayesian (VB) extension of the space-alternating generalized expectation-maximization (SAGE) algorithm for the high resolution estimation of the parameters of relevant multipath components in the response of frequency and spatially selective wireless...... channels. The application context of the algorithm considered in this contribution is parameter estimation from channel sounding measurements for radio channel modeling purpose. The new sparse VB-SAGE algorithm extends the classical SAGE algorithm in two respects: i) by monotonically minimizing...... parametric sparsity priors for the weights of the multipath components. We revisit the Gaussian sparsity priors within the sparse VB-SAGE framework and extend the results by considering Laplace priors. The structure of the VB-SAGE algorithm allows for an analytical stability analysis of the update expression...

Conflict Resolution in Computer Systems

Directory of Open Access Journals (Sweden)

G. P. Mojarov

2015-01-01

shortcoming in preventing impasses is a need to have a priori information on the future demand for resources, and it is not always possible.One of ways to "struggle" against impasses when there is no a priori information on the process demand for resources is to detect deadlocks. Detection of impasses (without leading to their resolution yet is a periodical use of the algorithm which checks current distribution of resources to reveal whether there is an impasse and if it exists what processes are involved in it.The work objective is to develop methods and algorithms allowing us to minimize losses because of impasses in CS using the optimum strategy of conflict resolution. The offered approach is especially effective to eliminate deadlocks in management (control computer systems having a fixed set of programmes.The article offers a developed efficient strategy of the information processes management in multiprocessing CS, which detects and prevents impasses. The strategy is based on allocation of indivisible resources to computing processes so that losses caused by conflicts are minimized. The article studies a multi-criterion problem of indivisible resources allocation to the processes, with the optimality principle expressed by the known binary relation over set of average vectors of penalties for conflicts in each of resources. It is shown that sharing a decision theory tool and a classical one allows more efficient problem solution to eliminate deadlock. The feature of suggesting effective methods and algorithms to eliminate deadlocks is that they can be used in CS development and operation in real time. The article-given example shows that the proposed method and algorithm for the impasse resolution in multiprocessing CS are capable and promising.The offered method and algorithm provide reducing the average number of CS conflicts by 30-40 %.

Mean-variance analysis of block-iterative reconstruction algorithms modeling 3D detector response in SPECT

Science.gov (United States)

Lalush, D. S.; Tsui, B. M. W.

1998-06-01

We study the statistical convergence properties of two fast iterative reconstruction algorithms, the rescaled block-iterative (RBI) and ordered subset (OS) EM algorithms, in the context of cardiac SPECT with 3D detector response modeling. The Monte Carlo method was used to generate nearly noise-free projection data modeling the effects of attenuation, detector response, and scatter from the MCAT phantom. One thousand noise realizations were generated with an average count level approximating a typical T1-201 cardiac study. Each noise realization was reconstructed using the RBI and OS algorithms for cases with and without detector response modeling. For each iteration up to twenty, we generated mean and variance images, as well as covariance images for six specific locations. Both OS and RBI converged in the mean to results that were close to the noise-free ML-EM result using the same projection model. When detector response was not modeled in the reconstruction, RBI exhibited considerably lower noise variance than OS for the same resolution. When 3D detector response was modeled, the RBI-EM provided a small improvement in the tradeoff between noise level and resolution recovery, primarily in the axial direction, while OS required about half the number of iterations of RBI to reach the same resolution. We conclude that OS is faster than RBI, but may be sensitive to errors in the projection model. Both OS-EM and RBI-EM are effective alternatives to the EVIL-EM algorithm, but noise level and speed of convergence depend on the projection model used.

Classifying spatially heterogeneous wetland communities using machine learning algorithms and spectral and textural features.

Science.gov (United States)

Szantoi, Zoltan; Escobedo, Francisco J; Abd-Elrahman, Amr; Pearlstine, Leonard; Dewitt, Bon; Smith, Scot

2015-05-01

Mapping of wetlands (marsh vs. swamp vs. upland) is a common remote sensing application.Yet, discriminating between similar freshwater communities such as graminoid/sedge fromremotely sensed imagery is more difficult. Most of this activity has been performed using medium to low resolution imagery. There are only a few studies using highspatial resolutionimagery and machine learning image classification algorithms for mapping heterogeneouswetland plantcommunities. This study addresses this void by analyzing whether machine learning classifierssuch as decisiontrees (DT) and artificial neural networks (ANN) can accurately classify graminoid/sedgecommunities usinghigh resolution aerial imagery and image texture data in the Everglades National Park, Florida.In addition tospectral bands, the normalized difference vegetation index, and first- and second-order texturefeatures derivedfrom the near-infrared band were analyzed. Classifier accuracies were assessed using confusiontablesand the calculated kappa coefficients of the resulting maps. The results indicated that an ANN(multilayerperceptron based on backpropagation) algorithm produced a statistically significantly higheraccuracy(82.04%) than the DT (QUEST) algorithm (80.48%) or the maximum likelihood (80.56%)classifier (αtexture features.

Discrimination of Biomass Burning Smoke and Clouds in MAIAC Algorithm

Science.gov (United States)

Lyapustin, A.; Korkin, S.; Wang, Y.; Quayle, B.; Laszlo, I.

2012-01-01

The multi-angle implementation of atmospheric correction (MAIAC) algorithm makes aerosol retrievals from MODIS data at 1 km resolution providing information about the fine scale aerosol variability. This information is required in different applications such as urban air quality analysis, aerosol source identification etc. The quality of high resolution aerosol data is directly linked to the quality of cloud mask, in particular detection of small (sub-pixel) and low clouds. This work continues research in this direction, describing a technique to detect small clouds and introducing the smoke test to discriminate the biomass burning smoke from the clouds. The smoke test relies on a relative increase of aerosol absorption at MODIS wavelength 0.412 micrometers as compared to 0.47-0.67 micrometers due to multiple scattering and enhanced absorption by organic carbon released during combustion. This general principle has been successfully used in the OMI detection of absorbing aerosols based on UV measurements. This paper provides the algorithm detail and illustrates its performance on two examples of wildfires in US Pacific North-West and in Georgia/Florida of 2007.

An efficient multi-resolution GA approach to dental image alignment

Science.gov (United States)

Nassar, Diaa Eldin; Ogirala, Mythili; Adjeroh, Donald; Ammar, Hany

2006-02-01

Automating the process of postmortem identification of individuals using dental records is receiving an increased attention in forensic science, especially with the large volume of victims encountered in mass disasters. Dental radiograph alignment is a key step required for automating the dental identification process. In this paper, we address the problem of dental radiograph alignment using a Multi-Resolution Genetic Algorithm (MR-GA) approach. We use location and orientation information of edge points as features; we assume that affine transformations suffice to restore geometric discrepancies between two images of a tooth, we efficiently search the 6D space of affine parameters using GA progressively across multi-resolution image versions, and we use a Hausdorff distance measure to compute the similarity between a reference tooth and a query tooth subject to a possible alignment transform. Testing results based on 52 teeth-pair images suggest that our algorithm converges to reasonable solutions in more than 85% of the test cases, with most of the error in the remaining cases due to excessive misalignments.

Optimization model of conventional missile maneuvering route based on improved Floyd algorithm

Science.gov (United States)

Wu, Runping; Liu, Weidong

2018-04-01

Missile combat plays a crucial role in the victory of war under high-tech conditions. According to the characteristics of maneuver tasks of conventional missile units in combat operations, the factors influencing road maneuvering are analyzed. Based on road distance, road conflicts, launching device speed, position requirements, launch device deployment, Concealment and so on. The shortest time optimization model was built to discuss the situation of road conflict and the strategy of conflict resolution. The results suggest that in the process of solving road conflict, the effect of node waiting is better than detour to another way. In this study, we analyzed the deficiency of the traditional Floyd algorithm which may limit the optimal way of solving road conflict, and put forward the improved Floyd algorithm, meanwhile, we designed the algorithm flow which would be better than traditional Floyd algorithm. Finally, throgh a numerical example, the model and the algorithm were proved to be reliable and effective.

Improved Passive Microwave Algorithms for North America and Eurasia

Science.gov (United States)

Foster, James; Chang, Alfred; Hall, Dorothy

1997-01-01

Microwave algorithms simplify complex physical processes in order to estimate geophysical parameters such as snow cover and snow depth. The microwave radiances received at the satellite sensor and expressed as brightness temperatures are a composite of contributions from the Earth's surface, the Earth's atmosphere and from space. Owing to the coarse resolution inherent to passive microwave sensors, each pixel value represents a mixture of contributions from different surface types including deep snow, shallow snow, forests and open areas. Algorithms are generated in order to resolve these mixtures. The accuracy of the retrieved information is affected by uncertainties in the assumptions used in the radiative transfer equation (Steffen et al., 1992). One such uncertainty in the Chang et al., (1987) snow algorithm is that the snow grain radius is 0.3 mm for all layers of the snowpack and for all physiographic regions. However, this is not usually the case. The influence of larger grain sizes appears to be of more importance for deeper snowpacks in the interior of Eurasia. Based on this consideration and the effects of forests, a revised SMMR snow algorithm produces more realistic snow mass values. The purpose of this study is to present results of the revised algorithm (referred to for the remainder of this paper as the GSFC 94 snow algorithm) which incorporates differences in both fractional forest cover and snow grain size. Results from the GSFC 94 algorithm will be compared to the original Chang et al. (1987) algorithm and to climatological snow depth data as well.

Optimization of the spatial resolution for the GE discovery PET/CT 710 by using NEMA NU 2-2007 standards

Science.gov (United States)

Yoon, Hyun Jin; Jeong, Young Jin; Son, Hye Joo; Kang, Do-Young; Hyun, Kyung-Yae; Lee, Min-Kyung

2015-01-01

The spatial resolution in positron emission tomography (PET) is fundamentally limited by the geometry of the detector element, the positron's recombination range with electrons, the acollinearity of the positron, the crystal decoding error, the penetration into the detector ring, and the reconstruction algorithms. In this paper, optimized parameters are suggested to produce high-resolution PET images by using an iterative reconstruction algorithm. A phantom with three point sources structured with three capillary tubes was prepared with an axial extension of less than 1 mm and was filled with 18F-fluorodeoxyglucose (18F-FDG) with concentrations above 200 MBq/cc. The performance measures of all the PET images were acquired according to the National Electrical Manufacturers Association (NEMA) NU 2-2007 standards procedures. The parameters for the iterative reconstruction were adjusted around the values recommended by General Electric GE, and the optimized values of the spatial resolution and the full width at half maximum (FWHM) or the full width at tenth of maximum (FWTM) values were found for the best PET resolution. The axial and the transverse spatial resolutions, according to the filtered back-projection (FBP) at 1 cm off-axis, were 4.81 and 4.48 mm, respectively. The axial and the transaxial spatial resolutions at 10 cm off-axis were 5.63 mm and 5.08 mm, respectively, and the trans-axial resolution at 10 cm was evaluated as the average of the radial and the tangential measurements. The recommended optimized parameters of the spatial resolution according to the NEMA phantom for the number of subsets, the number of iterations, and the Gaussian post-filter are 12, 3, and 3 mm for the iterative reconstruction VUE Point HD without the SharpIR algorithm (HD), and 12, 12, and 5.2 mm with SharpIR (HD.S), respectively, according to the Advantage Workstation Volume Share 5 (AW4.6). The performance measurements for the GE Discovery PET/CT 710 using the NEMA NU 2

Performance of a high resolution cavity beam position monitor system

Science.gov (United States)

Walston, Sean; Boogert, Stewart; Chung, Carl; Fitsos, Pete; Frisch, Joe; Gronberg, Jeff; Hayano, Hitoshi; Honda, Yosuke; Kolomensky, Yury; Lyapin, Alexey; Malton, Stephen; May, Justin; McCormick, Douglas; Meller, Robert; Miller, David; Orimoto, Toyoko; Ross, Marc; Slater, Mark; Smith, Steve; Smith, Tonee; Terunuma, Nobuhiro; Thomson, Mark; Urakawa, Junji; Vogel, Vladimir; Ward, David; White, Glen

2007-07-01

It has been estimated that an RF cavity Beam Position Monitor (BPM) could provide a position measurement resolution of less than 1 nm. We have developed a high resolution cavity BPM and associated electronics. A triplet comprised of these BPMs was installed in the extraction line of the Accelerator Test Facility (ATF) at the High Energy Accelerator Research Organization (KEK) for testing with its ultra-low emittance beam. The three BPMs were each rigidly mounted inside an alignment frame on six variable-length struts which could be used to move the BPMs in position and angle. We have developed novel methods for extracting the position and tilt information from the BPM signals including a robust calibration algorithm which is immune to beam jitter. To date, we have demonstrated a position resolution of 15.6 nm and a tilt resolution of 2.1 μrad over a dynamic range of approximately ±20 μm.

Real-time haptic cutting of high-resolution soft tissues.

Science.gov (United States)

Wu, Jun; Westermann, Rüdiger; Dick, Christian

2014-01-01

We present our systematic efforts in advancing the computational performance of physically accurate soft tissue cutting simulation, which is at the core of surgery simulators in general. We demonstrate a real-time performance of 15 simulation frames per second for haptic soft tissue cutting of a deformable body at an effective resolution of 170,000 finite elements. This is achieved by the following innovative components: (1) a linked octree discretization of the deformable body, which allows for fast and robust topological modifications of the simulation domain, (2) a composite finite element formulation, which thoroughly reduces the number of simulation degrees of freedom and thus enables to carefully balance simulation performance and accuracy, (3) a highly efficient geometric multigrid solver for solving the linear systems of equations arising from implicit time integration, (4) an efficient collision detection algorithm that effectively exploits the composition structure, and (5) a stable haptic rendering algorithm for computing the feedback forces. Considering that our method increases the finite element resolution for physically accurate real-time soft tissue cutting simulation by an order of magnitude, our technique has a high potential to significantly advance the realism of surgery simulators.

Sparsity-Based Super Resolution for SEM Images.

Science.gov (United States)

Tsiper, Shahar; Dicker, Or; Kaizerman, Idan; Zohar, Zeev; Segev, Mordechai; Eldar, Yonina C

2017-09-13

The scanning electron microscope (SEM) is an electron microscope that produces an image of a sample by scanning it with a focused beam of electrons. The electrons interact with the atoms in the sample, which emit secondary electrons that contain information about the surface topography and composition. The sample is scanned by the electron beam point by point, until an image of the surface is formed. Since its invention in 1942, the capabilities of SEMs have become paramount in the discovery and understanding of the nanometer world, and today it is extensively used for both research and in industry. In principle, SEMs can achieve resolution better than one nanometer. However, for many applications, working at subnanometer resolution implies an exceedingly large number of scanning points. For exactly this reason, the SEM diagnostics of microelectronic chips is performed either at high resolution (HR) over a small area or at low resolution (LR) while capturing a larger portion of the chip. Here, we employ sparse coding and dictionary learning to algorithmically enhance low-resolution SEM images of microelectronic chips-up to the level of the HR images acquired by slow SEM scans, while considerably reducing the noise. Our methodology consists of two steps: an offline stage of learning a joint dictionary from a sequence of LR and HR images of the same region in the chip, followed by a fast-online super-resolution step where the resolution of a new LR image is enhanced. We provide several examples with typical chips used in the microelectronics industry, as well as a statistical study on arbitrary images with characteristic structural features. Conceptually, our method works well when the images have similar characteristics, as microelectronics chips do. This work demonstrates that employing sparsity concepts can greatly improve the performance of SEM, thereby considerably increasing the scanning throughput without compromising on analysis quality and resolution.

J-substitution algorithm in magnetic resonance electrical impedance tomography (MREIT): phantom experiments for static resistivity images.

Science.gov (United States)

Khang, Hyun Soo; Lee, Byung Il; Oh, Suk Hoon; Woo, Eung Je; Lee, Soo Yeol; Cho, Min Hyoung; Kwon, Ohin; Yoon, Jeong Rock; Seo, Jin Keun

2002-06-01

Recently, a new static resistivity image reconstruction algorithm is proposed utilizing internal current density data obtained by magnetic resonance current density imaging technique. This new imaging method is called magnetic resonance electrical impedance tomography (MREIT). The derivation and performance of J-substitution algorithm in MREIT have been reported as a new accurate and high-resolution static impedance imaging technique via computer simulation methods. In this paper, we present experimental procedures, denoising techniques, and image reconstructions using a 0.3-tesla (T) experimental MREIT system and saline phantoms. MREIT using J-substitution algorithm effectively utilizes the internal current density information resolving the problem inherent in a conventional EIT, that is, the low sensitivity of boundary measurements to any changes of internal tissue resistivity values. Resistivity images of saline phantoms show an accuracy of 6.8%-47.2% and spatial resolution of 64 x 64. Both of them can be significantly improved by using an MRI system with a better signal-to-noise ratio.

A methodology for finding the optimal iteration number of the SIRT algorithm for quantitative Electron Tomography

Energy Technology Data Exchange (ETDEWEB)

Okariz, Ana, E-mail: ana.okariz@ehu.es [eMERG, Fisika Aplikatua I Saila, Faculty of Engineering, University of the Basque Country, UPV/EHU, Rafael Moreno “Pitxitxi” Pasealekua 3, 48013 Bilbao (Spain); Guraya, Teresa [eMERG, Departamento de Ingeniería Minera y Metalúrgica y Ciencia de los Materiales, Faculty of Engineering, University of the Basque Country, UPV/EHU, Rafael Moreno “Pitxitxi” Pasealekua 3, 48013 Bilbao (Spain); Iturrondobeitia, Maider [eMERG, Departamento de Expresión Gráfica y Proyectos de Ingeniería, Faculty of Engineering, University of the Basque Country, UPV/EHU, Rafael Moreno “Pitxitxi” Pasealekua 3, 48013 Bilbao (Spain); Ibarretxe, Julen [eMERG, Fisika Aplikatua I Saila, Faculty of Engineering,University of the Basque Country, UPV/EHU, Rafael Moreno “Pitxitxi” Pasealekua 2, 48013 Bilbao (Spain)

2017-02-15

The SIRT (Simultaneous Iterative Reconstruction Technique) algorithm is commonly used in Electron Tomography to calculate the original volume of the sample from noisy images, but the results provided by this iterative procedure are strongly dependent on the specific implementation of the algorithm, as well as on the number of iterations employed for the reconstruction. In this work, a methodology for selecting the iteration number of the SIRT reconstruction that provides the most accurate segmentation is proposed. The methodology is based on the statistical analysis of the intensity profiles at the edge of the objects in the reconstructed volume. A phantom which resembles a a carbon black aggregate has been created to validate the methodology and the SIRT implementations of two free software packages (TOMOJ and TOMO3D) have been used. - Highlights: • The non uniformity of the resolution in electron tomography reconstructions has been demonstrated. • An overall resolution for the evaluation of the quality of electron tomography reconstructions has been defined. • Parameters for estimating an overall resolution across the reconstructed volume have been proposed. • The overall resolution of the reconstructions of a phantom has been estimated from the probability density functions. • It has been proven that reconstructions with the best overall resolutions have provided the most accurate segmentations.

A methodology for finding the optimal iteration number of the SIRT algorithm for quantitative Electron Tomography

International Nuclear Information System (INIS)

Okariz, Ana; Guraya, Teresa; Iturrondobeitia, Maider; Ibarretxe, Julen

2017-01-01

The SIRT (Simultaneous Iterative Reconstruction Technique) algorithm is commonly used in Electron Tomography to calculate the original volume of the sample from noisy images, but the results provided by this iterative procedure are strongly dependent on the specific implementation of the algorithm, as well as on the number of iterations employed for the reconstruction. In this work, a methodology for selecting the iteration number of the SIRT reconstruction that provides the most accurate segmentation is proposed. The methodology is based on the statistical analysis of the intensity profiles at the edge of the objects in the reconstructed volume. A phantom which resembles a a carbon black aggregate has been created to validate the methodology and the SIRT implementations of two free software packages (TOMOJ and TOMO3D) have been used. - Highlights: • The non uniformity of the resolution in electron tomography reconstructions has been demonstrated. • An overall resolution for the evaluation of the quality of electron tomography reconstructions has been defined. • Parameters for estimating an overall resolution across the reconstructed volume have been proposed. • The overall resolution of the reconstructions of a phantom has been estimated from the probability density functions. • It has been proven that reconstructions with the best overall resolutions have provided the most accurate segmentations.

Refinement procedure for the image alignment in high-resolution electron tomography

International Nuclear Information System (INIS)

Houben, L.; Bar Sadan, M.

2011-01-01

High-resolution electron tomography from a tilt series of transmission electron microscopy images requires an accurate image alignment procedure in order to maximise the resolution of the tomogram. This is the case in particular for ultra-high resolution where even very small misalignments between individual images can dramatically reduce the fidelity of the resultant reconstruction. A tomographic-reconstruction based and marker-free method is proposed, which uses an iterative optimisation of the tomogram resolution. The method utilises a search algorithm that maximises the contrast in tomogram sub-volumes. Unlike conventional cross-correlation analysis it provides the required correlation over a large tilt angle separation and guarantees a consistent alignment of images for the full range of object tilt angles. An assessment based on experimental reconstructions shows that the marker-free procedure is competitive to the reference of marker-based procedures at lower resolution and yields sub-pixel accuracy even for simulated high-resolution data. -- Highlights: → Alignment procedure for electron tomography based on iterative tomogram contrast optimisation. → Marker-free, independent of object, little user interaction. → Accuracy competitive with fiducial marker methods and suited for high-resolution tomography.

Temporal resolution and motion artifacts in single-source and dual-source cardiac CT.

Science.gov (United States)

Schöndube, Harald; Allmendinger, Thomas; Stierstorfer, Karl; Bruder, Herbert; Flohr, Thomas

2013-03-01

The temporal resolution of a given image in cardiac computed tomography (CT) has so far mostly been determined from the amount of CT data employed for the reconstruction of that image. The purpose of this paper is to examine the applicability of such measures to the newly introduced modality of dual-source CT as well as to methods aiming to provide improved temporal resolution by means of an advanced image reconstruction algorithm. To provide a solid base for the examinations described in this paper, an extensive review of temporal resolution in conventional single-source CT is given first. Two different measures for assessing temporal resolution with respect to the amount of data involved are introduced, namely, either taking the full width at half maximum of the respective data weighting function (FWHM-TR) or the total width of the weighting function (total TR) as a base of the assessment. Image reconstruction using both a direct fan-beam filtered backprojection with Parker weighting as well as using a parallel-beam rebinning step are considered. The theory of assessing temporal resolution by means of the data involved is then extended to dual-source CT. Finally, three different advanced iterative reconstruction methods that all use the same input data are compared with respect to the resulting motion artifact level. For brevity and simplicity, the examinations are limited to two-dimensional data acquisition and reconstruction. However, all results and conclusions presented in this paper are also directly applicable to both circular and helical cone-beam CT. While the concept of total TR can directly be applied to dual-source CT, the definition of the FWHM of a weighting function needs to be slightly extended to be applicable to this modality. The three different advanced iterative reconstruction methods examined in this paper result in significantly different images with respect to their motion artifact level, despite exactly the same amount of data being used

Temporal resolution and motion artifacts in single-source and dual-source cardiac CT

International Nuclear Information System (INIS)

Schöndube, Harald; Allmendinger, Thomas; Stierstorfer, Karl; Bruder, Herbert; Flohr, Thomas

2013-01-01

Purpose: The temporal resolution of a given image in cardiac computed tomography (CT) has so far mostly been determined from the amount of CT data employed for the reconstruction of that image. The purpose of this paper is to examine the applicability of such measures to the newly introduced modality of dual-source CT as well as to methods aiming to provide improved temporal resolution by means of an advanced image reconstruction algorithm. Methods: To provide a solid base for the examinations described in this paper, an extensive review of temporal resolution in conventional single-source CT is given first. Two different measures for assessing temporal resolution with respect to the amount of data involved are introduced, namely, either taking the full width at half maximum of the respective data weighting function (FWHM-TR) or the total width of the weighting function (total TR) as a base of the assessment. Image reconstruction using both a direct fan-beam filtered backprojection with Parker weighting as well as using a parallel-beam rebinning step are considered. The theory of assessing temporal resolution by means of the data involved is then extended to dual-source CT. Finally, three different advanced iterative reconstruction methods that all use the same input data are compared with respect to the resulting motion artifact level. For brevity and simplicity, the examinations are limited to two-dimensional data acquisition and reconstruction. However, all results and conclusions presented in this paper are also directly applicable to both circular and helical cone-beam CT. Results: While the concept of total TR can directly be applied to dual-source CT, the definition of the FWHM of a weighting function needs to be slightly extended to be applicable to this modality. The three different advanced iterative reconstruction methods examined in this paper result in significantly different images with respect to their motion artifact level, despite exactly the same

An easy-to-implement and efficient data assimilation method for the identification of the initial condition: the Back and Forth Nudging (BFN) algorithm

International Nuclear Information System (INIS)

Auroux, Didier; Bansart, Patrick; Blum, Jacques

2008-01-01

This paper deals with a new data assimilation algorithm called the Back and Forth Nudging. The standard nudging technique consists in adding to the model equations a relaxation term, which is supposed to force the model to the observations. The BFN algorithm consists of repeating forward and backward resolutions of the model with relaxation (or nudging) terms, that have opposite signs in the direct and inverse resolutions, so as to make the backward evolution numerically stable. We then applied the Back and Forth Nudging algorithm to a simple non-linear model: the ID viscous Burgers' equations. The tests were carried out through several cases relative to the precision and density of the observations. These simulations were then compared with both the variational assimilation (VAR) and quasi-inverse (QIL) algorithms. The comparisons deal with the programming, the convergence, and time computing for each of these three algorithms.

An easy-to-implement and efficient data assimilation method for the identification of the initial condition: the Back and Forth Nudging (BFN) algorithm

Energy Technology Data Exchange (ETDEWEB)

Auroux, Didier [Institut de Mathematiques, Universite Paul Sabatier Toulouse 3, 31062 Toulouse cedex 9 (France); Bansart, Patrick; Blum, Jacques [Laboratoire J. A. Dieudonne, Universite de Nice Sophia-Antipolis, Pare Valrose, 06108 Nice cedex 2 (France)], E-mail: didier.auroux@math.univ-toulouse.fr

2008-11-01

This paper deals with a new data assimilation algorithm called the Back and Forth Nudging. The standard nudging technique consists in adding to the model equations a relaxation term, which is supposed to force the model to the observations. The BFN algorithm consists of repeating forward and backward resolutions of the model with relaxation (or nudging) terms, that have opposite signs in the direct and inverse resolutions, so as to make the backward evolution numerically stable. We then applied the Back and Forth Nudging algorithm to a simple non-linear model: the ID viscous Burgers' equations. The tests were carried out through several cases relative to the precision and density of the observations. These simulations were then compared with both the variational assimilation (VAR) and quasi-inverse (QIL) algorithms. The comparisons deal with the programming, the convergence, and time computing for each of these three algorithms.