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Готові списки джерел за темами / Distortion estimation / Статті в журналах

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Статті в журналах з теми "Distortion estimation"

Автор: Grafiati

Опубліковано: 11 березня 2023

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1

Peng, Z. K., G. Meng, and F. L. Chu. "Improved Wavelet Reassigned Scalograms and Application for Modal Parameter Estimation." Shock and Vibration 18, no. 1-2 (2011): 299–316. http://dx.doi.org/10.1155/2011/590741.

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The present work carries out a comprehensive investigation into the border distortion deficiency for the conventional scalogram and the reassigned scalogram. The reasons for this deficiency are analyzed, and a simple way is suggested to determine the border distortion ranges. New methods are proposed to reduce the border distortions in both the scalograms. The practical meanings of the border distortion improvement method are demonstrated by applying both the scalograms with and without border distortion improvements to estimate the modal parameters for a 2-DOF linear system. The estimation results indicate that, in the presence of noise, which is inevitable in practice, for the mode with weak amplitude, the reassigned scalogram can perform better than the conventional scalogram in estimating the modal parameters. In addition, for the mode with short effective duration, its frequency components at the border distortion ranges are of great importance for the modal parameter estimation purpose, and the border distortion improvement method can greatly increase the estimation accuracy.

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2

Chin, Sin Chee, Chee-Onn Chow, Jeevan Kanesan, and Joon Huang Chuah. "A Study on Distortion Estimation Based on Image Gradients." Sensors 22, no. 2 (January 14, 2022): 639. http://dx.doi.org/10.3390/s22020639.

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Image noise is a variation of uneven pixel values that occurs randomly. A good estimation of image noise parameters is crucial in image noise modeling, image denoising, and image quality assessment. To the best of our knowledge, there is no single estimator that can predict all noise parameters for multiple noise types. The first contribution of our research was to design a noise data feature extractor that can effectively extract noise information from the image pair. The second contribution of our work leveraged other noise parameter estimation algorithms that can only predict one type of noise. Our proposed method, DE-G, can estimate additive noise, multiplicative noise, and impulsive noise from single-source images accurately. We also show the capability of the proposed method in estimating multiple corruptions.

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3

Zhang, Qiuwen, Liang Tian, Lixun Huang, Xiaobing Wang, and Haodong Zhu. "Rendering Distortion Estimation Model for 3D High Efficiency Depth Coding." Mathematical Problems in Engineering 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/940737.

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A depth map represents three-dimensional (3D) scene geometry information and is used for depth image based rendering (DIBR) to synthesize arbitrary virtual views. Since the depth map is only used to synthesize virtual views and is not displayed directly, the depth map needs to be compressed in a certain way that can minimize distortions in the rendered views. In this paper, a modified distortion estimation model is proposed based on view rendering distortion instead of depth map distortion itself and can be applied to the high efficiency video coding (HEVC) rate distortion cost function process for rendering view quality optimization. Experimental results on various 3D video sequences show that the proposed algorithm provides about 31% BD-rate savings in comparison with HEVC simulcast and 1.3 dB BD-PSNR coding gain for the rendered view.

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4

Liao, Kang, Chunyu Lin, and Yao Zhao. "A Deep Ordinal Distortion Estimation Approach for Distortion Rectification." IEEE Transactions on Image Processing 30 (2021): 3362–75. http://dx.doi.org/10.1109/tip.2021.3061283.

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5

Sankisa, Arun, Katerina Pandremmenou, Peshala V. Pahalawatta, Lisimachos P. Kondi, and Aggelos K. Katsaggelos. "SSIM-Based Distortion Estimation for Optimized Video Transmission over Inherently Noisy Channels." International Journal of Multimedia Data Engineering and Management 7, no. 3 (July 2016): 34–52. http://dx.doi.org/10.4018/ijmdem.2016070103.

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The authors present two methods for examining video quality using the Structural Similarity (SSIM) index: Iterative Distortion Estimate (IDE) and Cumulative Distortion using SSIM (CDSSIM). In the first method, three types of slices are iteratively reconstructed frame-by-frame for three different combinations of packet loss and the resulting distortions are combined using their probabilities to give the total expected distortion. In the second method, a cumulative measure of the overall distortion is computed by summing the inter-frame propagation impact to all frames affected by a slice loss. Furthermore, the authors develop a No-Reference (NR) sparse regression framework for predicting the CDSSIM metric to circumvent the real-time computational complexity in streaming video applications. The two methods are evaluated in resource allocation and packet prioritization schemes and experimental results show improved performance and better end-user quality. The accuracy of the predicted CDSSIM values is studied using standard performance measures and a Quartile-Based Prioritization (QBP) scheme.

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6

MA, LILI, YANGQUAN CHEN, and KEVIN L. MOORE. "RATIONAL RADIAL DISTORTION MODELS OF CAMERA LENSES WITH ANALYTICAL SOLUTION FOR DISTORTION CORRECTION." International Journal of Information Acquisition 01, no. 02 (June 2004): 135–47. http://dx.doi.org/10.1142/s0219878904000173.

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The common approach to radial distortion is by the means of polynomial approximation, which introduces distortion-specific parameters into the camera model and requires estimation of these distortion parameters. The task of estimating radial distortion is to find a radial distortion model that allows easy undistortion as well as satisfactory accuracy. This paper presents a new class of rational radial distortion models with easy analytical undistortion formulae. Experimental results are presented to show that with this class of rational radial distortion models, satisfactory and comparable accuracy can be achieved.

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7

Tsukahara, H. "Estimation of Distortion Risk Measures." Journal of Financial Econometrics 12, no. 1 (March 19, 2013): 213–35. http://dx.doi.org/10.1093/jjfinec/nbt005.

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8

Guo, Kai, Hu Ye, Honglin Chen, and Xin Gao. "A New Method for Absolute Pose Estimation with Unknown Focal Length and Radial Distortion." Sensors 22, no. 5 (February 25, 2022): 1841. http://dx.doi.org/10.3390/s22051841.

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Анотація:

Estimating the absolute pose of a camera is one of the key steps for computer vision. In some cases, especially when using a wide-angle or zoom lens, the focal length and radial distortion also need to be considered. Therefore, in this paper, an efficient and robust method for a single solution is proposed to estimate the absolute pose for a camera with unknown focal length and radial distortion, using three 2D–3D point correspondences and known camera position. The problem is decomposed into two sub-problems, which makes the estimation simpler and more efficient. The first sub-problem is to estimate the focal length and radial distortion. An important geometric characteristic of radial distortion, that the orientation of the 2D image point with respect to the center of distortion (i.e., principal point in this paper) under radial distortion is unchanged, is used to solve this sub-problem. The focal length and up to four-order radial distortion can be determined with this geometric characteristic, and it can be applied to multiple distortion models. The values with no radial distortion are used as the initial values, which are close to the global optimal solutions. Then, the sub-problem can be efficiently and accurately solved with the initial values. The second sub-problem is to determine the absolute pose with geometric linear constraints. After estimating the focal length and radial distortion, the undistorted image can be obtained, and then the absolute pose can be efficiently determined from the point correspondences and known camera position using the undistorted image. Experimental results indicate this method’s accuracy and numerical stability for pose estimation with unknown focal length and radial distortion in synthetic data and real images.

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9

Ayof, Mohamad Nizam, Ruzaini Mohd Nawi, Nur Izan Syahriah Hussein, and Nor Zulaikha Zainol. "Distortion Prediction of Welded Thin Plate Lap Joints by Finite Element Analysis and Experiment." Key Engineering Materials 796 (March 2019): 175–82. http://dx.doi.org/10.4028/www.scientific.net/kem.796.175.

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Welding process is an efficient joining process of metals that is achieved by gas metal arc welding (GMAW) process. Localized heating during welding process can result in distortion of the welded plate. The estimation of magnitude and distribution of distortion are important to maintain the quality of products. Finite element method is implemented to investigate the distortions behavior of thin steel plate, cold rolled (SPCC) material in lap joint using GMAW process. A three-dimensional, two-step thermomechanical finite element model study was applied to analyze and evaluate distortion behavior in lap joint. The result of distortion from finite element analysis (FEA) was compared to experimental data to validate the accuracy of the method.

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10

Tong, Jonathan, Robert S. Allison, and Laurie M. Wilcox. "The Impact of Radial Distortions in VR Headsets on Perceived Surface Slant." Journal of Imaging Science and Technology 63, no. 6 (November 1, 2019): 60409–1. http://dx.doi.org/10.2352/j.imagingsci.technol.2019.63.6.060409.

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Abstract Modern virtual reality (VR) headsets use lenses that distort the visual field, typically with distortion increasing with eccentricity. While content is pre-warped to counter this radial distortion, residual image distortions remain. Here we examine the extent to which such residual distortion impacts the perception of surface slant. In Experiment 1, we presented slanted surfaces in a head-mounted display and observers estimated the local surface slant at different locations. In Experiments 2 (slant estimation) and 3 (slant discrimination), we presented stimuli on a mirror stereoscope, which allowed us to more precisely control viewing and distortion parameters. Taken together, our results show that radial distortion has significant impact on perceived surface attitude, even following correction. Of the distortion levels we tested, 5% distortion results in significantly underestimated and less precise slant estimates relative to distortion-free surfaces. In contrast, Experiment 3 reveals that a level of 1% distortion is insufficient to produce significant changes in slant perception. Our results highlight the importance of adequately modeling and correcting lens distortion to improve VR user experience.

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11

Hartley, R., and Sing Bing Kang. "Parameter-Free Radial Distortion Correction with Center of Distortion Estimation." IEEE Transactions on Pattern Analysis and Machine Intelligence 29, no. 8 (August 2007): 1309–21. http://dx.doi.org/10.1109/tpami.2007.1147.

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12

MOHAMMADI, SHAPOUR. "EFFECT OF OUTLIERS ON THE FRACTAL DIMENSION ESTIMATION." Fractals 19, no. 02 (June 2011): 233–41. http://dx.doi.org/10.1142/s0218348x11005324.

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Анотація:

The effect of outliers on estimation of the fractal dimension of experimental chaotic and stock market stochastic data series is investigated. The results indicate that influential observations of a magnitude of mean ±5 standard deviations can lead to a distortion of fractal dimension estimations by as much as 40% for short (e.g. 500 observations) time series data. Moreover, the box dimension estimation method is more sensitive to outliers than information and correlation dimension estimation methods and the effect of outliers decreases as the number of observations increases. Application of outlier adjustment to the stock prices of 60 companies of the Dow Jones Industrial Index reveals that the effect of outliers is critical in estimating the fractal dimension. The fractal dimension has applications in risk analysis for financial markets that can be affected by outliers.

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13

Liang, D. W., and S. Y. Zhang. "Estimation of the maximum instantaneous distortion." Journal of Propulsion and Power 8, no. 1 (January 1992): 5–6. http://dx.doi.org/10.2514/3.23434.

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14

Wing-Kin Ma and Yuan-Ting Zhang. "Estimation of distortion product otoacoustic emissions." IEEE Transactions on Biomedical Engineering 46, no. 10 (1999): 1261–64. http://dx.doi.org/10.1109/10.790504.

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15

Harrison, Matthew T., and Ioannis Kontoyiannis. "Estimation of the Rate–Distortion Function." IEEE Transactions on Information Theory 54, no. 8 (August 2008): 3757–62. http://dx.doi.org/10.1109/tit.2008.926387.

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16

Yue, Zhenming, Houssem Badreddine, Khemais Saanouni, Xincun Zhuang, and Jun Gao. "Numerical simulation of sheet metal blanking based on fully coupled elastoplasticity-damage constitutive equations accounting for yield surface distortion-induced anisotropy." International Journal of Damage Mechanics 26, no. 7 (October 16, 2016): 1061–79. http://dx.doi.org/10.1177/1056789516673886.

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Анотація:

This paper deals with the numerical simulation of sheet metal blanking process based on fully coupled elastoplastic model accounting for the induced anisotropies due to the kinematic hardening and the yield surface distortion. The yield surface distortion is assumed to be controlled by the kinematic hardening leading additional extra hardening which enhances the predictive capabilities of the model. Series of finite element-based numerical simulations of blanking process with four kinds of assumed distortional hardening parameters have been conducted. Through the comparison between the experimentally observed responses and the numerically predicted ones with and without the yield surface distortion effect, the significance of the yield surface distortion-induced anisotropy on the estimation of the blanking edge quality has been investigated.

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17

Hou, Wentao, Fengjun Zhao, Xiuqing Liu, Dacheng Liu, Yonghui Han, Yao Gao, and Robert Wang. "Hybrid Compact Polarimetric SAR Calibration Considering the Amplitude and Phase Coefficients Inconsistency." Remote Sensing 14, no. 2 (January 17, 2022): 416. http://dx.doi.org/10.3390/rs14020416.

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Calibration using corner reflectors is an effective way to estimate the distortion parameters of hybrid compact polarimetric (HCP) synthetic aperture radar (SAR) systems. However, the existing literature lacks a discussion on the inconsistency of the amplitude and phase coefficients between measured scattering vectors of different corner reflectors. In response to this problem, this paper first proves that this inconsistency will seriously deteriorate the estimation accuracy of polarimetric distortion parameters. Based on the optimization algorithm, two calibration schemes for simultaneously estimating the traditional distortion parameters and the amplitude/phase coefficients are proposed while ignoring crosstalk (ICT) and considering crosstalk (CCT). In the process of distortion parameter estimation, the idea of “optimizing while compensating” is adopted to eliminate the problem of uneven echo intensity. Simulation results show that both schemes can eliminate the influence of the inconsistency of amplitude and phase coefficients, and estimate distortion parameters accurately. When the received crosstalk level is lower than −30 dB, the ICT scheme can accurately estimate polarimetric distortion parameters. The CCT scheme has a wider application range of crosstalk and can work well when the crosstalk level is lower than −20 dB, but it also has a higher requirement for the signal-to-clutter ratio (SCR). When SCR is greater than 35 dB, the CCT scheme yields higher estimation accuracy than the ICT scheme. In addition, the effectiveness of the calibration schemes is verified based on the L-band measured data acquired by the Aerospace Information Research Institute, Chinese Academy of Sciences.

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18

Laws, Kenneth, Jeffrey D. Paduan, and John Vesecky. "Estimation and Assessment of Errors Related to Antenna Pattern Distortion in CODAR SeaSonde High-Frequency Radar Ocean Current Measurements." Journal of Atmospheric and Oceanic Technology 27, no. 6 (June 1, 2010): 1029–43. http://dx.doi.org/10.1175/2009jtecho658.1.

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Abstract A simulation-based investigation of errors in HF radar–derived, near-surface ocean current measurements is presented. The simulation model is specific to Coastal Ocean Dynamics Application Radar (CODAR) SeaSonde radar systems that employ a compact, collocated antenna geometry. In this study, radial current retrievals are obtained by processing simulated data using unmodified CODAR data processing software. To avoid limiting the results to specific ocean current and wind wave scenarios, the analyses employ large ensembles of randomly varying simulated environmental conditions. The effect of antenna pattern distortion on the accuracy of retrievals is investigated using 40 different antenna sensitivity patterns of varying levels of distortion. A single parameter is derived to describe the level of the antenna pattern distortion. This parameter is found to be highly correlated with the rms error of the simulated radial currents (r = 0.94) and therefore can be used as a basis for evaluating the severity of site-specific antenna pattern distortions. Ensemble averages of the subperiod simulated current retrieval standard deviations are found to be highly correlated with the antenna pattern distortion parameter (r = 0.92). Simulations without distortions of the antenna pattern indicate that an rms radial current error of 2.9 cm s−1 is a minimum bound on the error of a SeaSonde ocean radar system, given a typical set of operating parameters and a generalized ensemble of ocean conditions.

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19

Xue, J. S., X. N. Chen, and H. Yi. "A ROBUST METHOD FOR FUNDAMENTAL MATRIX ESTIMATION WITH RADIAL DISTORTION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (April 30, 2018): 2029–33. http://dx.doi.org/10.5194/isprs-archives-xlii-3-2029-2018.

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Fundamental Matrix Estimation is of vital importance in many vision applications and is a core part of 3D reconstruction pipeline. Radial distortion makes the problem to be numerically challenging. We propose a novel robust method for radial fundamental matrix estimation. Firstly, two-sided radial fundamental matrix is deduced to describe epipolar geometry relationship between two distorted images. Secondly, we use singular value decomposition to solve the final nonlinear minimization solutions and to get the outliers removed by multiplying a weighted matrix to the coefficient matrix. In every iterative step, the criterion which is the distance between feature point and corresponding epipolar line is used to determine the inliers and the weighted matrix is update according to it. The iterative process has a fast convergence rate, and the estimation result of radial fundamental matrix remains stable even at the condition of many outliers. Experimental results prove that the proposed method is of high accuracy and robust for estimating the radial fundamental matrix. The estimation result of radial fundamental matrix could be served as the initialization for structure from motion.

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20

Lipatkin, V. I., E. M. Lobov, and E. O. Lobova. "THE QUALITY OF ESTIMATION OF PARAMETERS OF A BROADBAND SIGNAL WITH NON-OPTIMAL RECEPTION UNDER CONDITIONS OF DISPERSION DISTORTIONS IN THE EARTH'S IONOSPHERE." T-Comm 16, no. 8 (2022): 46–53. http://dx.doi.org/10.36724/2072-8735-2022-16-8-46-53.

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In the article, analytical expressions are obtained that make it possible to calculate the variance of the estimates of the initial phase, frequency and delay of the signal, as well as the covariance functions of pairs of estimates under the conditions of dispersion distortions. At the same time, the evaluating device does not know exactly or does not know the level of dispersion distortions at all and does not try to evaluate them. Therefore, the estimation of the parameters is carried out by a non-optimal algorithm. The described conditions arise in practice, for example, when trying to estimate the above parameters of a broadband signal by a classical estimator that does not take into account dispersion distortions. The described conditions also occur when the true value of the slope of the dispersion characteristic of the channel deviates from the previously measured value over time or due to the use of inaccurate measurement results or an inaccurate prediction of the value of the slope of the dispersion characteristic of the channel. The article presents analytically obtained graphs for the root-mean-square deviations of the obtained phase, delay and frequency estimates for the case of complete absence of dispersion distortion compensation and the case of incomplete dispersion distortion compensation. In particular, it is shown that the degradation of the quality of delay estimation is due to two factors: a value decrease and an expansion of the correlation peak. In terms of energy, this degradation exceeds the acquisition or demodulation loss. The results of the obtained calculations are confirmed by simulation modeling.

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21

HOMMA, Koichi, and Fuminobu KOMURA. "An Estimation and Correction Method of Geometrical Distortion by Shifting the Distortion." Transactions of the Society of Instrument and Control Engineers 23, no. 12 (1987): 1239–45. http://dx.doi.org/10.9746/sicetr1965.23.1239.

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22

Wang, Aiqi, Tianshuang Qiu, and Longtan Shao. "A Simple Method of Radial Distortion Correction with Centre of Distortion Estimation." Journal of Mathematical Imaging and Vision 35, no. 3 (July 7, 2009): 165–72. http://dx.doi.org/10.1007/s10851-009-0162-1.

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23

Barliani, Amridon G., Galina A. Nefedova, and Irina V. Karnetova. "STUDY OF THE ALGORITHM OF PSEUDONORMAL OPTIMIZATION ON THE STABILITY OF THE SOLUTION OF THE EQUATION PROBLEM AND THE ESTIMATION OF THE ACCURACY." Interexpo GEO-Siberia 1 (May 21, 2021): 40–48. http://dx.doi.org/10.33764/2618-981x-2021-1-40-48.

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In geodesic practice, when designing and adjusting geodetic networks for various purposes on a computer, it is necessary to solve poorly conditioned systems of linear normal equations. In such systems, the determinant of the matrix of equations tends to zero, so the application of the least squares method leads to large distortions of the estimated parameters. Moreover, in such situations, for the least squares algorithm, a slight distortion of the input data leads to unacceptably large distortions of the final results of the equalization and accuracy estimation. In this regard, the application of the pseudonormal optimization method is proposed. The presented work is devoted to the study of the stability of the solution of the adjustment task and the estimation of accuracy obtained on the basis of the pseudonormal optimization method. The novelty is the obtained algorithm for estimating the relative error of the pseudonormal optimization method. A comparative analysis of two competing processing methods was performed for different network models. The results of experimental studies and their analysis have shown the advantage of the pseudonormal optimization method over the least squares method.

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24

Okumoto, Yasuhisa, and Shigeo Eguchi. "Estimation of Welding Distortion Using Neural Network." Journal of the Japan Society of Naval Architects and Ocean Engineers 2 (2005): 149–54. http://dx.doi.org/10.2534/jjasnaoe.2.149.

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25

Okumoto, Yasuhisa. "Estimation of Welding Distortion Using Neural Network." Journal of Ship Production 24, no. 04 (November 1, 2008): 190–95. http://dx.doi.org/10.5957/jsp.2008.24.4.190.

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Recently, the prediction of welding distortion of steel structure has been carried out widely. Though the thermal elastic-plasticity finite element method (FEM) analysis is usually required to ensure the accuracy of the estimation, technical knowledge is required, and long computing time is necessary. In this study, simplification of the prediction was done using a neural network model, in which the calculation result of the FEM analysis was incorporated in teacher data, for the fillet welding of T-type buildup structure, etc. This program would be able to estimate the welding distortion of the joint with different dimensions and welding conditions in a simple manner.

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26

Agha, S., V. M. Dwyer, and V. Chouliaras. "Motion estimation with low resolution distortion metric." Electronics Letters 41, no. 12 (2005): 693. http://dx.doi.org/10.1049/el:20050481.

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27

Alam, Mohammad S. "Multireference joint transform correlator for distortion estimation." Optical Engineering 37, no. 1 (January 1, 1998): 38. http://dx.doi.org/10.1117/1.601853.

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28

Min, Xiongkuo, Guangtao Zhai, Ke Gu, Yutao Liu, and Xiaokang Yang. "Blind Image Quality Estimation via Distortion Aggravation." IEEE Transactions on Broadcasting 64, no. 2 (June 2018): 508–17. http://dx.doi.org/10.1109/tbc.2018.2816783.

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29

Zhang, X. H., W. S. Lin, and P. Xue. "Improved estimation for just-noticeable visual distortion." Signal Processing 85, no. 4 (April 2005): 795–808. http://dx.doi.org/10.1016/j.sigpro.2004.12.002.

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30

Zahneisen, Benjamin, Kathrin Baeumler, Greg Zaharchuk, Dominik Fleischmann, and Michael Zeineh. "Deep flow-net for EPI distortion estimation." NeuroImage 217 (August 2020): 116886. http://dx.doi.org/10.1016/j.neuroimage.2020.116886.

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31

Tian, Yuandong, and Srinivasa G. Narasimhan. "Globally Optimal Estimation of Nonrigid Image Distortion." International Journal of Computer Vision 98, no. 3 (December 21, 2011): 279–302. http://dx.doi.org/10.1007/s11263-011-0509-0.

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32

KIM, J. S., and L. S. KIM. "Binary Motion Estimation with Hybrid Distortion Measure." IEICE Transactions on Information and Systems E90-D, no. 9 (September 1, 2007): 1474–77. http://dx.doi.org/10.1093/ietisy/e90-d.9.1474.

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33

Grenson, Pierre, and Eric Garnier. "Distortion reconstruction in S-ducts from wall static pressure measurements." International Journal of Numerical Methods for Heat & Fluid Flow 28, no. 5 (May 8, 2018): 1134–55. http://dx.doi.org/10.1108/hff-06-2017-0232.

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Анотація:

Purpose This paper aims to report the attempts for predicting “on-the-fly” flow distortion in the engine entrance plane of a highly curved S-duct from wall static pressure measurements. Such a technology would be indispensable to trigger active flow control devices to mitigate the intense flow separations which occur in specific flight conditions. Design/methodology/approach Evaluation of different reconstruction algorithms is performed on the basis of data extracted from a Zonal Detached Eddy Simulation (ZDES) of a well-documented S-Duct (Garnier et al., AIAA J., 2015). Contrary to RANS methods, such a hybrid approach makes unsteady distortions available, which are necessary information for reconstruction algorithm assessment. Findings The best reconstruction accuracy is obtained with the artificial neural network (ANN) but the improvement compared to the classical linear stochastic estimation (LSE) is minor. The different inlet distortion coefficients are not reconstructed with the same accuracy. KA2 coefficient is finally identified as the more suited for activation of the control device. Originality/value LSE and its second-order variant (quadratic stochastic estimation [QSE]) are applied for reconstructing instantaneous stagnation pressure in the flow field. The potential improvement of an algorithm based on an ANN is also evaluated. The statistical link between the wall sensors and 40-Kulite rake sensors are carefully discussed and the accuracy of the reconstruction of the most used distortion coefficients (DC60, RDI, CDI and KA2) is quantified for each estimation technique.

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34

He, Shu Qian, Zheng Jie Deng, and Chun Shi. "A Novel Header Bits Estimation Scheme for H.264/AVC Standard." Applied Mechanics and Materials 333-335 (July 2013): 787–90. http://dx.doi.org/10.4028/www.scientific.net/amm.333-335.787.

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Rate estimation is useful for many H.264/AVC applications including rate-distortion optimization (RDO) for fast mode decision and precise rate control. In this paper, we propose a new header rate prediction model and an adaptive algorithm to provide more accurate estimation of the number of total coding bits for rate control compared to previously proposed methods. The header bit rate estimation is modeled by a linear combination of the number of mode block, and the sum of absolute values of all motion vectors for each block. Based on the proposed model, a header rate estimation function is also proposed to give a more accurate rate-distortion rate control. The proposed schemes can achieve better results in rate-distortion and rate control to previously proposed approaches.

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35

Kakani, Vijay, Hakil Kim, Jongseo Lee, Choonwoo Ryu, and Mahendar Kumbham. "Automatic Distortion Rectification of Wide-Angle Images Using Outlier Refinement for Streamlining Vision Tasks." Sensors 20, no. 3 (February 7, 2020): 894. http://dx.doi.org/10.3390/s20030894.

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The study proposes an outlier refinement methodology for automatic distortion rectification of wide-angle and fish-eye lens camera models in the context of streamlining vision-based tasks. The line-members sets are estimated in a scene through accumulation of line candidates emerging from the same edge source. An iterative optimization with an outlier refinement scheme was applied to the loss value, to simultaneously remove the extremely curved outliers from the line-members set and update the robust line members as well as estimating the best-fit distortion parameters with lowest possible loss. The proposed algorithm was able to rectify the distortions of wide-angle and fish-eye cameras even in extreme conditions such as heavy illumination changes and severe lens distortions. Experiments were conducted using various evaluation metrics both at the pixel-level (image quality, edge stretching effects, pixel-point error) as well as higher-level use-cases (object detection, height estimation) with respect to real and synthetic data from publicly available, privately acquired sources. The performance evaluations of the proposed algorithm have been investigated using an ablation study on various datasets in correspondence to the significance analysis of the refinement scheme and loss function. Several quantitative and qualitative comparisons were carried out on the proposed approach against various self-calibration approaches.

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36

Guo, Xiaoxi, Alex S. Leong, and Subhrakanti Dey. "Distortion Outage Minimization in Distributed Estimation With Estimation Secrecy Outage Constraints." IEEE Transactions on Signal and Information Processing over Networks 3, no. 1 (March 2017): 12–28. http://dx.doi.org/10.1109/tsipn.2016.2612122.

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37

Alegria, Francisco C. "Precision of the Sinefitting-Based Total Harmonic Distortion Estimator." Metrology and Measurement Systems 23, no. 1 (March 1, 2016): 37–46. http://dx.doi.org/10.1515/mms-2016-0003.

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Abstract An analytical expression for the standard deviation of Total Harmonic Distortion (THD) estimation is derived. It applies to the case where the estimator uses sine fitting. It is shown that, in common circumstances, it is inversely proportional to the actual value of THD, the signal-to-noise ratio and the square root of the number of samples. The proposed expression is validated both with numerical simulations and an experimental setup using a Monte Carlo procedure.

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38

Chen, Qunlin, Derong Chen, and Jiulu Gong. "Low-Complexity Adaptive Sampling of Block Compressed Sensing Based on Distortion Minimization." Sensors 22, no. 13 (June 25, 2022): 4806. http://dx.doi.org/10.3390/s22134806.

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Block compressed sensing (BCS) is suitable for image sampling and compression in resource-constrained applications. Adaptive sampling methods can effectively improve the rate-distortion performance of BCS. However, adaptive sampling methods bring high computational complexity to the encoder, which loses the superiority of BCS. In this paper, we focus on improving the adaptive sampling performance at the cost of low computational complexity. Firstly, we analyze the additional computational complexity of the existing adaptive sampling methods for BCS. Secondly, the adaptive sampling problem of BCS is modeled as a distortion minimization problem. We present three distortion models to reveal the relationship between block sampling rate and block distortion and use a simple neural network to predict the model parameters from several measurements. Finally, a fast estimation method is proposed to allocate block sampling rates based on distortion minimization. The results demonstrate that the proposed estimation method of block sampling rates is effective. Two of the three proposed distortion models can make the proposed estimation method have better performance than the existing adaptive sampling methods of BCS. Compared with the calculation of BCS at the sampling rate of 0.1, the additional calculation of the proposed adaptive sampling method is less than 1.9%.

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39

Lobov, Evgeniy M., Vladimir S. Priputin, Elizaveta O. Lobova, and Efim A. Liberman. "DISPERSION DISTORTION TRACKING COMPENSATOR BASED ON THE SIGMA-POINT KALMAN." T-Comm 15, no. 1 (2021): 41–47. http://dx.doi.org/10.36724/2072-8735-2021-15-1-41-47.

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The article proposes an algorithm for nonlinear optimal filtering of the dispersion characteristic slope of the ionospheric channel (DC slope) based on the Kalman sigma-point filter when sounding the channel with broadband signals. The relevance of the applied algorithm can be explained by the fact that at present in the modern world the relevance of the transmission of broadband information signals in the decameter range has increased. The reception of such signals is complicated by the effects caused by the influence of the frequency dispersion of the ionospheric channel on the signal. The above influence leads to significant distortions of the useful signal and a decrease in the quality of information reception in general. The above influence leads to significant distortions of the useful signal and a decrease in the quality of information reception in general. Therefore, the effect of frequency dispersion cannot be neglected and must be taken into account when developing algorithms for optimal reception. Thus, estimation of the parameters of the frequency dispersion of the ionospheric channel becomes an urgent task. The article provides recurrent formulas for calculating the optimal filtration of the DC slope. Moreover, an algorithm for joint estimation of dispersion distortions and their compensation is presented, which allows improving the quality of estimation. The results of simulation modeling of the algorithms are given: the obtained estimate and the true value of the frequency dispersion parameters for two cases – a Markov damped process and a process with random increments. The absolute error in estimating the DC slope is also considered. The computational efficiency of the algorithm for estimating the DC slope using the Kalman sigma-point filter with and without compensation is calculated. In addition, functional diagrams of optimal filtering of the DC slope with compensation and without compensation are given. The ways of implementing the proposed algorithm on an ARM processor are considered.

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40

Cruz, Angelo R. Dela, Ryan Rhay P. Vicerra, Argel A. Bandala, and Elmer P. Dadios. "Dynamic Rate Allocation Algorithm Using Adaptive LMS End-to-End Distortion Estimation for Video Transmission over Error Prone Network." Journal of Advanced Computational Intelligence and Intelligent Informatics 20, no. 1 (January 19, 2016): 106–10. http://dx.doi.org/10.20965/jaciii.2016.p0106.

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Because of the inherent trade-off between source distortion and channel distortion in video transmission systems, joint optimization between bit-rate and distortion is still a challenging task. In this paper, we propose a method where the bit-rate allocation between source and channel encoder is controlled by the estimated end-to-end distortion at the encoder. The distortion estimation scheme is based on the adaptive forward linear predictor using least-mean square (LMS) algorithm. The forward predictor used the past values of actual end-to-end distortion to estimate the current distortion. The results show good estimate of end-to-end distortion and the proposed scheme improves video quality as compared to a standard rate control of H.264/AVC. The proposed scheme dynamically allocates the source encoder bits based on the estimated distortion.

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41

Chen, Hong-Xiang, Kunhong Li, Zhiheng Fu, Mengyi Liu, Zonghao Chen, and Yulan Guo. "Distortion-Aware Monocular Depth Estimation for Omnidirectional Images." IEEE Signal Processing Letters 28 (2021): 334–38. http://dx.doi.org/10.1109/lsp.2021.3050712.

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42

Thormählen, Thorsten, and Hellward Broszio. "Automatic line-based estimation of radial lens distortion." Integrated Computer-Aided Engineering 12, no. 2 (April 5, 2005): 177–90. http://dx.doi.org/10.3233/ica-2005-12204.

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43

Liu, Liang-bing, Wei-hong Fang, Ai-she Shui, Jun Liu, and Li Zhang. "Mainlobe Spectrum Distortion and Its Self-estimation Algorithm." Journal of Electronics & Information Technology 35, no. 6 (February 17, 2014): 1512–15. http://dx.doi.org/10.3724/sp.j.1146.2012.01222.

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44

Ke-Ying Liao, Jar-Ferr Yang, and Ming-Ting Sun. "Rate-Distortion Cost Estimation for H.264/AVC." IEEE Transactions on Circuits and Systems for Video Technology 20, no. 1 (January 2010): 38–49. http://dx.doi.org/10.1109/tcsvt.2009.2026946.

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45

Arruda, Elcio F. de, Nelson Kagan, and Paulo F. Ribeiro. "Harmonic Distortion State Estimation Using an Evolutionary Strategy." IEEE Transactions on Power Delivery 25, no. 2 (April 2010): 831–42. http://dx.doi.org/10.1109/tpwrd.2009.2036922.

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46

Grbovic, Mihajlo, and Slobodan Vucetic. "Decentralized Estimation using distortion sensitive learning vector quantization." Pattern Recognition Letters 34, no. 9 (July 2013): 963–69. http://dx.doi.org/10.1016/j.patrec.2013.02.011.

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47

Cai, Zewei, Xiaoli Liu, Giancarlo Pedrini, Wolfgang Osten, and Xiang Peng. "Light-field depth estimation considering plenoptic imaging distortion." Optics Express 28, no. 3 (January 29, 2020): 4156. http://dx.doi.org/10.1364/oe.385285.

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48

Musierowicz, Kazimierz, and Wojciech Bandurski. "Estimation of protection's criterion values during arc distortion." International Journal of Electrical Power & Energy Systems 24, no. 9 (November 2002): 737–42. http://dx.doi.org/10.1016/s0142-0615(01)00088-6.

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49

Krishnapuram, Raghuram, and David Casasent. "Hough space transformations for discrimination and distortion estimation." Computer Vision, Graphics, and Image Processing 38, no. 3 (June 1987): 299–316. http://dx.doi.org/10.1016/0734-189x(87)90115-0.

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50

Jones, Bruce L., and Ričardas Zitikis. "Risk measures, distortion parameters, and their empirical estimation." Insurance: Mathematics and Economics 41, no. 2 (September 2007): 279–97. http://dx.doi.org/10.1016/j.insmatheco.2006.11.001.

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