Precomputed Lookup Tables Research Articles

Real-Time Dynamic Bokeh Rendering With Efficient Look-Up Table Sampling.

This article presents a real-time bokeh rendering technique that splats pre-computed sprites but takes dynamic visibilities and intrinsic appearances into account at runtime. To attain alias-free looks without excessive sampling on a lens, the visibilities of strong highlights are densely sampled using rasterization, while regular objects are sparsely sampled using conventional defocus-blur rendering. The intrinsic appearance is dynamically transformed from a precomputed look-up table, which encodes radial aberrations against image distances in a compact 2D texture. Our solution can render complex bokeh effects without undersampling artifacts in real time, and greatly improve the photorealism of defocus-blur rendering.

An accurate and efficient radiative transfer model for simulating all-sky images from Fengyun satellite radiometers

Forward radiative transfer models (RTM) are an indispensable tool for quantitative applications of satellite radiometers, e.g., for data calibration, instrument development, retrieval, and so on. In this study, we develop an accurate and efficient RTM for radiometers onboard Fengyun satellites, namely FYRTM (RTM for Fengyun Radiometers). Correlated k-distribution models are developed to improve the computational efficiency for gas absorption, and the effects of cloud and aerosol multiple scattering and emission are accelerated with pre-computed look-up tables. FYRTM is evaluated with a rigorous simulation based on discrete ordinate radiative transfer model (DISORT) as well as a popular fast forward model, i.e., the Community Radiative Transfer Model (CRTM). Results indicate that FYRTM-based simulations are two to three orders of magnitudes faster than the DISORT-based simulations. Compared to the rigorous model, FYRTM relative errors are within 2% at solar channels, and brightness temperatures (BT) differences are within 1 K at infrared channels. Compared with CRTM, FYRTM is computationally similar at solar channels, but three times faster at infrared channels. Furthermore, simulated reflectances/BTs using FYRTM are in a good agreement with the satellite observations. Overall, FYRTM is capable to simulate satellite observations under different atmospheric conditions, and can be extended to other radiometers onboard the Fengyun satellites (both geostationary and polar-orbiting satellites). It is expected to play important roles in future applications with Fengyun observations.

An Active Genomic Data Recovery Attack

With the decreasing cost and availability of human genome sequencing, genomic privacy becomes an important issue. Several methods have been proposed in the literature to overcome these problems including cryptographic and privacy preserving data mining methods: homomorphic encryption, cryptographic hardware. In a recent work, Barman et. al studied privacy threats and practical solutions considering an SNP based scenario. The authors introduced a new protocol where a malicious medical center processes an active attack in order to retrieve genomic data of a given patient. The authors have mentioned that this protocol provides a trade-off between privacy and practicality. In this paper, we first give an overview of the system for SNP based risk calculation. We provide the definitions of privacy threats and briefly Barman et al.’s protocol and their solution. The authors proposed to use a weighted sum method of SNP coefficients for calculating disease tendency. They argue that the specific choice of the bases would prevent unique identification of SNPs. Our main observation is that this is not true. Contrary to the security claim, SNP combinations can be identified uniquely in many different scenarios. Our method exploits a pre-computed look-up table for retrieving SNPs’ values from the test result. An attacker can obtain all SNP values of a given patient by using the pre-computed look-up table. We provide practical examples of weights and pre-computed tables. We also mention that even in the case where the table is large and the attacker can not handle at one time, he can still gather information using multi queries. Our work shows that more realistic attack scenarios must be considered in the design of genetic security systems.

WADA-W: A Modified WADA SNR Estimator for Audio-Visual Speech Recognition

One of the main challenges in speech recognition is developing systems that are robust to contamination by intrusive background noise. In audio-visual speech recognition (AVSR), audio information is augmented by visual information in order to help improve the performance of speech recognition, particularly when the audio modality is so significantly corrupted by background noise and it becomes hard to differentiate the original speech signal from the noise. The signal-to-noise ratio (SNR) can be used to identify the level of noise in original speech signal and one widely used method for SNR estimation is waveform amplitude distribution analysis (WADA), which is based on the assumption that the speech and noise signals have Gamma and Gaussian amplitude distributions respectively. Based on previous approaches, this work uses a precomputed look-up table as a reference for SNR estimation. In this study, WADA-white (WADA-W) has been developed, which rebuilds the precomputed look-up table using a white noise profile in combination of our own AVSR database. This new data corpus, namely the Loughborough University Audio-Visual (LUNA-V) dataset that contains recordings of 10 speakers with five sets of samples uttered by each speaker is used for this experimental work. We evaluate the performance of WADA-W on this database when it is corrupted by noise generated from three profiles obtained from the NOISEX-92 database included at varying SNR values. Evaluation of performance using the LUNA-V database shows that WADA-W performs better than the original WADA in terms of SNR estimation.

Systematic Design of Bandgap Voltage Reference Using Precomputed Lookup Tables

Bandgap voltage references are indispensable in any analog/mixed-signal system. In this paper, we introduce a systematic gm/ID-based procedure to design a CMOS bandgap reference. The proposed iterative methodology relies on one-time-generated precomputed lookup tables (LUTs); thus, it does not require invoking a simulator in the loop. Despite the inherent finite accuracy of the LUT-based design approach, we demonstrate that a precision bandgap circuit can be designed with less than 1-ppm error. We verified the proposed procedure against the Spectre simulations and probed the design space using a symbolic circuit solver. Moreover, we demonstrated how variations and mismatch can be taken into account in the context of the proposed methodology. The results demonstrate that the proposed procedure can provide very accurate results in a short execution time, enabling the designer to explore the design space of key performance metrics, such as power-supply rejection (PSR) and noise.

Discovering Genetic Factors for psoriasis through exhaustively searching for significant second order SNP-SNP interactions

In this paper, we aim at discovering genetic factors of psoriasis through searching for statistically significant SNP-SNP interactions exhaustively from two real psoriasis genome-wide association study datasets (phs000019.v1.p1 and phs000982.v1.p1) downloaded from the database of Genotypes and Phenotypes. To deal with the enormous search space, our search algorithm is accelerated with eight biological plausible interaction patterns and a pre-computed look-up table. After our search, we have discovered several SNPs having a stronger association to psoriasis when they are in combination with another SNP and these combinations may be non-linear interactions. Among the top 20 SNP-SNP interactions being found in terms of pairwise p-value and improvement metric value, we have discovered 27 novel potential psoriasis-associated SNPs where most of them are reported to be eQTLs of a number of known psoriasis-associated genes. On the other hand, we have inferred a gene network after selecting the top 10000 SNP-SNP interactions in terms of improvement metric value and we have discovered a novel long distance interaction between XXbac-BPG154L12.4 and RNU6-283P which is not a long distance haplotype and may be a new discovery. Finally, our experiments with the synthetic datasets have shown that our pre-computed look-up table technique can significantly speed up the search process.

Embedding hierarchical clustering in product quantization for feature indexing

Effective indexing is a crucial need for large scale object matching and retrieval. In this work, a novel indexing scheme is presented, that exploits the advantages of hierarchical clustering and product quantization. First, the high dimensional feature space is decomposed into disjointed sub-spaces and the data belonging to each sub-space is separately represented by a hierarchical clustering tree. Second, each tree quantizes a distinct part of an input vector to the closest centroid of a leaf node and the distances for all the pairs of centroids are pre-computed and stored in a lookup table. Finally, searching for a given query is proceeded in parallel between the trees and is performed efficiently in the quantized space using the pre-computed lookup tables. The proposed method has been validated by a number of experiments, demonstrating significant improvements of search performance in comparison with other methods.

Ultra-fast basic geometrical transformations on linear image data structure

Abstract This paper presents a general, ultra-fast approach for geometrical image transformations, based on the usage of linear lookup hash tables. The new method is developed to fix distortions on document images as part of a real-time optical character recognition (OCR) system. The approach is generalized and uses linear image representation combined with pre-computed lookup tables. Backward mapping is used for generation of lookup tables, while forward mapping is presented as an alternative and more efficient mapping model for specific cases. Also, a theoretical space and time complexity analysis of the proposed method is provided. To achieve maximal computational performance, pointer arithmetic and highly-optimized low-level machine code implementations are provided, including the specialized implementations for horizontal mirror, vertical mirror, and 90° rotation. Also, a modified variant of the approach, based on auto-generated machine code is presented. Very high computational performances are achieved at the expense of memory usage. The performances from the perspective of time complexity are analyzed and compared with classical implementation, FPGA implementation, and other implementations of the image rotation. Numerical results are given for a set of different PC specifications to provide full insight into the implementation performances. The processing time for very large images are below 200 ms for backward mapping and below 100 ms for forward mapping for most machines, which is 30–60 times faster than the classical implementation, 5–20 times faster than the FPGA implementation, and up to 6 times faster than other implementations of image rotation. Original documents belonging to Nikola Tesla are used for visual demonstration of performance.

Interferometer angle‐of‐arrival determination using precalculated phases

AbstractA method has been developed to determine the angle of arrival (AoA) of incident radiation using precomputed lookup tables. The phase difference between two receiving antennas can be used to infer AoA as measured from the pair baseline, but there will be more than one possible solution for antenna spacings greater than or equal to half a wavelength. Larger spacings are preferable to minimize mutual coupling of elements in the receive array and to decrease the relative uncertainty in measured phase difference. We present a solution that uses all unique antenna pairs to determine probabilities for all possible azimuth and zenith values. Prior to analysis, the expected phase differences for all AoAs are calculated for each antenna pair. For a received signal, histograms of possible AoAs for each antenna pair phase difference are extracted and added to produce a two‐dimensional probability density array that will maximize at the true value of the AoA. A benefit of this method is that all possible antenna pairs are utilized rather than the restriction to specific pairs along baselines used by some interferometer algorithms. Numerical simulations indicate that performance of the suggested algorithm exceeds that of existing methods, with the benefit of additional flexibility in antenna placement. Meteor radar data have been used to test this method against existing methods, with excellent agreement between the two approaches. This method of AoA determination will allow the construction of low‐cost interferometric direction finding arrays with different layouts, including construction of difficult terrain and three‐dimensional antenna arrangements.

Near Vacuum Gas Damping in MEMS: Simplified Modeling

We propose a simplified, fast, and operative simulation tool for the prediction of gas damping occurring in the microelectromechanical systems (MEMS) of arbitrarily complex geometry and motion, working in near vacuum in a pressure range around 1 mbar. The tool is based on precomputed lookup tables (distributed with the paper), providing dissipation for the elemental blocks of MEMS. Next, adopting a decoupling assumption, blocks are combined according to the topology of the device to be analyzed. Particular attention is devoted to the validation of working hypotheses using numerical data generated by a refined model, data taken from the literature for simple test devices, and new experimental results for industrial gyroscopes.

Spatial Interpolated Lookup Tables (LUTs) Models for Ergodic Capacity of MIMO FSO Systems

We propose low complexity, adaptive multivariate precomputed B-spline and Barycentric Lagrange interpolation-based lookup table ( $ {B}^{2}$ LUT) models for the estimation of channel capacity of multiple-input-multiple-output free-space optical communication systems over generalized Malaga $( {\mathcal{ M}})$ -distributed atmospheric turbulence channels. The models require low memory for efficient operation and exploit precomputed weights to achieve fast and stable operation. The models can significantly reduce the size of lookup table, thereby reducing the computational cost. Similarly, the models can enhance the speed by up to 15 orders of magnitude and beyond without loss of fidelity compared with the current analytical models.

Optimized Cross-Layered Unequal Error Protection for SPIHT Coded Wireless Video Transmission

Transmission of coded video over erroneous channels (e.g., Internet and wireless networks) is always a challenging task. Error control strategies, to combat the channel errors, are generally applied at individual network layers leading to inefficient utilization of resources. The cross-layer design has emerged as alternative for efficient utilization of the available resources, such as bandwidth, delay, and transmission power to provide best quality of the reconstructed video. Furthermore, to efficiently utilize the resources, cross-layer error control parameters need to be optimized. Since, the optimal error control parameters change with channel conditions, new optimal values need to be calculated every time the channel condition changes. However, optimization of the parameters at the time of video transmission requires very high computational processing power otherwise it may induce a large transmission delay which is intolerable in video communication. In this paper, we propose an optimized cross-layered unequal error protection (UEP) scheme targeted for hand-held devices which have low processing power, uses pre-computed look-up table (LUT) that stores the optimal cross-layer error control parameters for a range of channel conditions. LUT is constructed using offline optimization of the parameters. For real time video communication, given a channel condition, the corresponding error control parameters are read from a LUT and are passed to the corresponding network layers. Thus, the proposed transmission system is simple and delivers best end-to-end quality of the video. Simulation results show that the proposed cross-layered UEP system can achieve up to 14–17 dB and 2–4 dB improvement in video quality over individual application layer optimized UEPs in additive white Gaussian noise and fading channel respectively at very poor channel conditions. Furthermore, the proposed system outperforms other contemporary methods.

User controllable anisotropic shape distribution on 3D meshes

This paper presents an automatic method for computing an anisotropic 2D shape distribution on an arbitrary 2-manifold mesh. Our method allows the user to specify the direction as well as the density of the distribution. Using a pre-computed lookup table, our method can efficiently detect collision among the shapes to be distributed on the 3D mesh. In contrast to existing approaches, which usually assume the 2D objects are isotropic and have simple geometry, our method works for complex 2D objects and can guarantee the distribution is conflict-free, which is a critical constraint in many applications. It is able to compute multi-class shape distributions in parallel. Our method does not require global parameterization of the input 3D mesh. Instead, it computes local parameterizations on the fly using geodesic polar coordinates. Thanks to a recent breakthrough in geodesic computation, the local parameterization can be computed at low cost. As a result, our method can be applied to models with complicated geometry and topology. Experimental results on a wide range of 3D models and 2D anisotropic shapes demonstrate the good performance and effectiveness of our method.

Frequency and causes of failed MODIS cloud property retrievals for liquid phase clouds over global oceans.

Moderate Resolution Imaging Spectroradiometer (MODIS) retrieves cloud droplet effective radius (r e) and optical thickness (τ) by projecting observed cloud reflectances onto a precomputed look‐up table (LUT). When observations fall outside of the LUT, the retrieval is considered “failed” because no combination of τ and r e within the LUT can explain the observed cloud reflectances. In this study, the frequency and potential causes of failed MODIS retrievals for marine liquid phase (MLP) clouds are analyzed based on 1 year of Aqua MODIS Collection 6 products and collocated CALIOP and CloudSat observations. The retrieval based on the 0.86 µm and 2.1 µm MODIS channel combination has an overall failure rate of about 16% (10% for the 0.86 µm and 3.7 µm combination). The failure rates are lower over stratocumulus regimes and higher over the broken trade wind cumulus regimes. The leading type of failure is the “r e too large” failure accounting for 60%–85% of all failed retrievals. The rest is mostly due to the “r e too small” or τ retrieval failures. Enhanced retrieval failure rates are found when MLP cloud pixels are partially cloudy or have high subpixel inhomogeneity, are located at special Sun‐satellite viewing geometries such as sunglint, large viewing or solar zenith angles, or cloudbow and glory angles, or are subject to cloud masking, cloud overlapping, and/or cloud phase retrieval issues. The majority (more than 84%) of failed retrievals along the CALIPSO track can be attributed to at least one or more of these potential reasons. The collocated CloudSat radar reflectivity observations reveal that the remaining failed retrievals are often precipitating. It remains an open question whether the extremely large r e values observed in these clouds are the consequence of true cloud microphysics or still due to artifacts not included in this study.

Obstacle-Avoiding Algorithm in X-Architecture Based on Discrete Particle Swarm Optimization for VLSI Design

Obstacle-avoiding Steiner minimal tree (OASMT) construction has become a focus problem in the physical design of modern very large-scale integration (VLSI) chips. In this article, an effective algorithm is presented to construct an OASMT based on X-architecturex for a given set of pins and obstacles. First, a kind of special particle swarm optimization (PSO) algorithm is proposed that successfully combines the classic genetic algorithm (GA), and greatly improves its own search capability. Second, a pretreatment strategy is put forward to deal with obstacles and pins, which can provide a fast information inquiry for the whole algorithm by generating a precomputed lookup table. Third, we present an efficient adjustment method, which enables particles to avoid all the obstacles by introducing some corner points of obstacles. Finally, an excellent refinement method is discussed to further enhance the quality of the final routing tree, which can improve the quality of the solution by 7.93% on average. To our best knowledge, this is the first time to specially solve the single-layer obstacle-avoiding problem in X-architecture. Experimental results show that the proposed algorithm can further shorten wirelength in the presence of obstacles. And it achieves the best solution quality in a reasonable runtime among the existing algorithms.

A depolarisation lidar-based method for the determination of liquid-cloud microphysical properties

Abstract. The fact that polarisation lidars measure a depolarisation signal in liquid clouds due to the occurrence of multiple scattering is well known. The degree of measured depolarisation depends on the lidar characteristics (e.g. wavelength and receiver field of view) as well as the cloud macrophysical (e.g. cloud-base altitude) and microphysical (e.g. effective radius, liquid water content) properties. Efforts seeking to use depolarisation information in a quantitative manner to retrieve cloud properties have been undertaken with, arguably, limited practical success. In this work we present a retrieval procedure applicable to clouds with (quasi-)linear liquid water content (LWC) profiles and (quasi-)constant cloud-droplet number density in the cloud-base region. Thus limiting the applicability of the procedure allows us to reduce the cloud variables to two parameters (namely the derivative of the liquid water content with height and the extinction at a fixed distance above cloud base). This simplification, in turn, allows us to employ a fast and robust optimal-estimation inversion using pre-computed look-up tables produced using extensive lidar Monte Carlo (MC) multiple-scattering simulations. In this paper, we describe the theory behind the inversion procedure and successfully apply it to simulated observations based on large-eddy simulation (LES) model output. The inversion procedure is then applied to actual depolarisation lidar data corresponding to a range of cases taken from the Cabauw measurement site in the central Netherlands. The lidar results were then used to predict the corresponding cloud-base region radar reflectivities. In non-drizzling condition, it was found that the lidar inversion results can be used to predict the observed radar reflectivities with an accuracy within the radar calibration uncertainty (2–3 dBZ). This result strongly supports the accuracy of the lidar inversion results. Results of a comparison between ground-based aerosol number concentration and lidar-derived cloud-droplet number densities are also presented and discussed. The observed relationship between the two quantities is seen to be consistent with the results of previous studies based on aircraft-based in situ measurements.

Optimized Cartesian K-Means

Product quantization-based approaches are effective to encode high-dimensional data points for approximate nearest neighbor search. The space is decomposed into a Cartesian product of low-dimensional subspaces, each of which generates a sub codebook. Data points are encoded as compact binary codes using these sub codebooks, and the distance between two data points can be approximated efficiently from their codes by the precomputed lookup tables. Traditionally, to encode a subvector of a data point in a subspace, only one sub codeword in the corresponding sub codebook is selected, which may impose strict restrictions on the search accuracy. In this paper, we propose a novel approach, named optimized cartesian K-means (ock-means), to better encode the data points for more accurate approximate nearest neighbor search. In ock-means, multiple sub codewords are used to encode the subvector of a data point in a subspace. Each sub codeword stems from different sub codebooks in each subspace, which are optimally generated with regards to the minimization of the distortion errors. The high-dimensional data point is then encoded as the concatenation of the indices of multiple sub codewords from all the subspaces. This can provide more flexibility and lower distortion errors than traditional methods. Experimental results on the standard real-life data sets demonstrate the superiority over state-of-the-art approaches for approximate nearest neighbor search.

Integration by interpolation and look-up for Galerkin-based isogeometric analysis

Even though isogeometric analysis has a clear advantage regarding the number of degrees of freedom needed to achieve a certain level of accuracy, the time needed for matrix assembly (by means of numerical integration of stiffness or mass matrix entries) constitutes a severe bottleneck in the process. In order to overcome this difficulty, we propose the new approach of Integration by Interpolation and Lookup (IIL). Firstly, applying spline interpolation to the common factors in the occurring integrals approximately transforms them into integrals of piecewise polynomial functions, whose integrands are expressed in tensor-product B-spline form. The common factors represent the influence of the geometry mapping (i.e., the NURBS domain parameterization) and the contributions of possibly non-constant material coefficients. Secondly, these integrals are evaluated exactly using pre-computed look-up tables for integrals of tri-products of univariate B-splines and their derivatives. For the model case of elliptic problems, we perform a theoretical analysis to demonstrate that the IIL method maintains the overall approximation order of the Galerkin discretization, provided that the spline interpolation is sufficiently accurate. Moreover, we provide a comparison of the computational complexity of our method with that of a standard Gauss quadrature method. Finally, we present experimental results to illustrate the performance of the IIL method and to support our theoretical results.

TRIFORCE: Tessellated Semianalytical Solvent Exposed Surface Areas and Derivatives.

We present a new approach to the calculation of solvent-accessible surface areas of molecules with potential application to surface area based methods for determination of solvation free energies. As in traditional analytical and statistical approaches, this new algorithm, called TRIFORCE, reports both component areas and derivatives as a function of the atomic coordinates and radii. Unique to TRIFORCE are the rapid and scalable approaches for the determination of sphere intersection points and numerical estimation of the surface areas, derivatives, and other properties that can be associated with the surface area facets. The algorithm performs a special tessellation and semianalytical integration that uses a precomputed look-up table. This provides a simple way to balance numerical accuracy and memory usage. TRIFORCE calculates derivatives in the same manner, enabling application in force-dependent activities such as molecular geometry minimization. TRIFORCE is available free of charge for academic purposes as both a C++ library, which can be directly interfaced to existing molecular simulation packages, and a web-accessible application.

A novel method for estimating shortwave direct radiative effect of above-cloud aerosols using CALIOP and MODIS data

Abstract. This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) and MODIS (Moderate Resolution Imaging Spectroradiometer) data. It addresses the overlap of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure while also accounting for subgrid-scale variations of aerosols. The method is computationally efficient because of its use of grid-level cloud and aerosol statistics, instead of pixel-level products, and a precomputed look-up table based on radiative transfer calculations. We verify that for smoke and polluted dust over the southeastern Atlantic Ocean the method yields a seasonal mean instantaneous (approximately 13:30 local time) shortwave DRE of above-cloud aerosol (ACA) that generally agrees with a more rigorous pixel-level computation within 4%. We also estimate the impact of potential CALIOP aerosol optical depth (AOD) retrieval bias of ACA on DRE. We find that the regional and seasonal mean instantaneous DRE of ACA over southeastern Atlantic Ocean would increase, from the original value of 6.4 W m−2 based on operational CALIOP AOD to 9.6 W m−2 if CALIOP AOD retrievals are biased low by a factor of 1.5 (Meyer et al., 2013) and further to 30.9 W m−2 if CALIOP AOD retrievals are biased low by a factor of 5 as suggested in Jethva et al. (2014). In contrast, the instantaneous ACA radiative forcing efficiency (RFE) remains relatively invariant in all cases at about 53 W m−2 AOD−1, suggesting a near-linear relation between the instantaneous RFE and AOD. We also compute the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global oceans based on 4 years of CALIOP and MODIS data. We find that given an above-cloud aerosol type the optical depth of the underlying clouds plays a larger role than above-cloud AOD in the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol. While we demonstrate our method using CALIOP and MODIS data, it can also be extended to other satellite data sets.