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Artículos de revistas sobre el tema "Mellin and scale transform"

Autor: Grafiati

Publicado: 11 de marzo de 2023

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1

Pivarčiová, Elena, Daynier Rolando Delgado Sobrino, Yury Rafailovich Nikitin, Radovan Holubek, and Roman Ružarovský. "Measuring and evaluating the differences of compared images for a correct car silhouette categorization using integral transforms." Measurement Science Review 18, no. 4 (2018): 168–74. http://dx.doi.org/10.1515/msr-2018-0024.

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Abstract The present paper focuses on the analysis of the possibilities of using integral transforms for measuring and evaluating the differences of compared images (car silhouettes) with the purpose of a correct car body categorization. Approaches such as the light intensities frequency change, the application of discrete integral transforms without the use of further supplementary information enabling automated data processing using the Fourier-Mellin transforms are used within this work. The calculation of the several metrics was verified through different combinations that implied using an

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2

Xu, Qingwen, Haofei Kuang, Laurent Kneip, and Sören Schwertfeger. "Rethinking the Fourier-Mellin Transform: Multiple Depths in the Camera’s View." Remote Sensing 13, no. 5 (2021): 1000. http://dx.doi.org/10.3390/rs13051000.

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Remote sensing and robotics often rely on visual odometry (VO) for localization. Many standard approaches for VO use feature detection. However, these methods will meet challenges if the environments are feature-deprived or highly repetitive. Fourier-Mellin Transform (FMT) is an alternative VO approach that has been shown to show superior performance in these scenarios and is often used in remote sensing. One limitation of FMT is that it requires an environment that is equidistant to the camera, i.e., single-depth. To extend the applications of FMT to multi-depth environments, this paper prese

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3

Wang, Baocheng, Dandan Qu, Qing Tian, and Liping Pang. "Mellin Transform-Based Correction Method for Linear Scale Inconsistency of Intrusion Events Identification in OFPS." Photonic Sensors 8, no. 3 (2018): 220–27. http://dx.doi.org/10.1007/s13320-018-0486-9.

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4

VYAS, VIBHA S., and PRITI P. REGE. "GEOMETRIC TRANSFORM INVARIANT TEXTURE ANALYSIS WITH MODIFIED CHEBYSHEV MOMENTS BASED ALGORITHM." International Journal of Image and Graphics 09, no. 04 (2009): 559–74. http://dx.doi.org/10.1142/s0219467809003587.

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Texture based Geometric invariance, which comprises of rotation scale and translation (RST) invariant is finding application in various areas including industrial inspection, estimation of object range and orientation, shape analysis, satellite imaging, and medical diagnosis. Moments based techniques, apart from being computationally simple as compared to other RST invariant texture operators, are also robust in presence of noise. Zernike moments (ZM) based techniques are one of the well-established methods used for texture identification. As ZM are continuous moments, when discretization is d

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5

Monakov, A. A. "An Algorithm for Estimating the Velocity of a Moving Target Based on Mellin Matched Filter." Journal of the Russian Universities. Radioelectronics 25, no. 3 (2022): 22–38. http://dx.doi.org/10.32603/1993-8985-2022-25-3-22-38.

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Introduction. Construction of the radar image of a moving target and estimation of its velocity in synthetic aperture radars (SAR) presents a relevant research problem. The low quality of radar imaging is frequently related to the phenomenon of range cell migration (RCM). Conventional methods for RCM compensation, which are successfully used to obtain radar images of stationary targets, fail to provide the required quality when applied to moving targets. At present, a number of algorithms are used to solve this problem. However, the majority of them employ optimization procedures when searchin

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6

Chen, Hui-Chi. "Improved performance of scale-invariant pattern recognition using a combined Mellin radial harmonic function and wavelet transform." Optical Engineering 46, no. 10 (2007): 107204. http://dx.doi.org/10.1117/1.2799534.

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7

Monjur, Mehjabin Sultana, Shih Tseng, Renu Tripathi, and M. S. Shahriar. "Incorporation of polar Mellin transform in a hybrid optoelectronic correlator for scale and rotation invariant target recognition." Journal of the Optical Society of America A 31, no. 6 (2014): 1259. http://dx.doi.org/10.1364/josaa.31.001259.

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8

Lizzi, Fedele, Mattia Manfredonia та Flavio Mercati. "Localizability in κ-Minkowski spacetime". International Journal of Geometric Methods in Modern Physics 17, supp01 (2020): 2040010. http://dx.doi.org/10.1142/s0219887820400101.

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Using the methods of ordinary quantum mechanics, we study [Formula: see text]-Minkowski space as a quantum space described by noncommuting self-adjoint operators, following and enlarging T. Poulain and J.-C. Wallet, “[Formula: see text]-Poincaré invariant orientable field theories with at 1-loop: Scale-invariant couplings, preprint (2018), arXiv:1808.00350 [hep-th]. We see how the role of Fourier transforms is played in this case by Mellin transforms. We briefly discuss the role of transformations and observers.

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9

Padovese, L. R., N. Martin, and F. Millioz. "Time—frequency and time-scale analysis of Barkhausen noise signals." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 223, no. 5 (2009): 577–88. http://dx.doi.org/10.1243/09544100jaero436.

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Carrying out information about the microstructure and stress behaviour of ferromagnetic steels, magnetic Barkhausen noise (MBN) has been used as a basis for effective non-destructive testing methods, opening new areas in industrial applications. One of the factors that determines the quality and reliability of the MBN analysis is the way information is extracted from the signal. Commonly, simple scalar parameters are used to characterize the information content, such as amplitude maxima and signal root mean square. This paper presents a new approach based on the time—frequency analysis. The ex

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10

Sasiela, Richard J., and John D. Shelton. "Transverse spectral filtering and Mellin transform techniques applied to the effect of outer scale on tilt and tilt anisoplanatism." Journal of the Optical Society of America A 10, no. 4 (1993): 646. http://dx.doi.org/10.1364/josaa.10.000646.

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11

Kudryavtsev, Alexey, and Oleg Shestakov. "The Estimators of the Bent, Shape and Scale Parameters of the Gamma-Exponential Distribution and Their Asymptotic Normality." Mathematics 10, no. 4 (2022): 619. http://dx.doi.org/10.3390/math10040619.

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When modeling real phenomena, special cases of the generalized gamma distribution and the generalized beta distribution of the second kind play an important role. The paper discusses the gamma-exponential distribution, which is closely related to the listed ones. The asymptotic normality of the previously obtained strongly consistent estimators for the bent, shape, and scale parameters of the gamma-exponential distribution at fixed concentration parameters is proved. Based on these results, asymptotic confidence intervals for the estimated parameters are constructed. The statements are based o

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12

MIRJALILI, A., and K. KESHAVARZIAN. "THE NLO QCD CALCULATION OF SEA QUARK DISTRIBUTIONS IN THE CORGI APPROACH, BASED ON THE CONSTITUENT QUARK MODEL." International Journal of Modern Physics A 22, no. 24 (2007): 4519–35. http://dx.doi.org/10.1142/s0217751x07037056.

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Sea quark distributions in the NLO approximation, based on the phenomenological valon model or constituent quark model are analyzed. We use the parametrized inverse Mellin transform technique to perform a direct fit with available experimental data and obtain the unknown parameters of the distributions. We try to extend the calculation to the NLO approximation for the singlet and nonsinglet cases in DIS phenomena. We do also the same calculation for electron–positron annihilation. The resulting sea distributions are effectively independent of the process used. The approach of complete RG impro

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13

Bülow, Heiko, and Andreas Birk. "Scale-Free Registrations in 3D: 7 Degrees of Freedom with Fourier Mellin SOFT Transforms." International Journal of Computer Vision 126, no. 7 (2018): 731–50. http://dx.doi.org/10.1007/s11263-018-1067-5.

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14

Lu, Huimin, Dan Xiong, Junhao Xiao, and Zhiqiang Zheng. "Robust long-term object tracking with adaptive scale and rotation estimation." International Journal of Advanced Robotic Systems 17, no. 2 (2020): 172988142090973. http://dx.doi.org/10.1177/1729881420909736.

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In this article, a robust long-term object tracking algorithm is proposed. It can tackle the challenges of scale and rotation changes during the long-term object tracking for security robots. Firstly, a robust scale and rotation estimation method is proposed to deal with scale changes and rotation motion of the object. It is based on the Fourier–Mellin transform and the kernelized correlation filter. The object’s scale and rotation can be estimated in the continuous space, and the kernelized correlation filter is used to improve the estimation accuracy and robustness. Then a weighted object se

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15

Zhao, Zeng-Shun, Xiang Feng, Sheng-Hua Teng, Yi-Bin Li, and Chang-Shui Zhang. "Multiscale Point Correspondence Using Feature Distribution and Frequency Domain Alignment." Mathematical Problems in Engineering 2012 (2012): 1–14. http://dx.doi.org/10.1155/2012/382369.

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In this paper, a hybrid scheme is proposed to find the reliable point-correspondences between two images, which combines the distribution of invariant spatial feature description and frequency domain alignment based on two-stage coarse to fine refinement strategy. Firstly, the source and the target images are both down-sampled by the image pyramid algorithm in a hierarchical multi-scale way. The Fourier-Mellin transform is applied to obtain the transformation parameters at the coarse level between the image pairs; then, the parameters can serve as the initial coarse guess, to guide the followi

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16

Xiao, Bin, Jian-Feng Ma, and Jiang-Tao Cui. "Combined blur, translation, scale and rotation invariant image recognition by Radon and pseudo-Fourier–Mellin transforms." Pattern Recognition 45, no. 1 (2012): 314–21. http://dx.doi.org/10.1016/j.patcog.2011.06.017.

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17

Meena, Kunj Bihari, and Vipin Tyagi. "A hybrid copy-move image forgery detection technique based on Fourier-Mellin and scale invariant feature transforms." Multimedia Tools and Applications 79, no. 11-12 (2020): 8197–212. http://dx.doi.org/10.1007/s11042-019-08343-0.

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18

Shimizu, Sota, and Joel W. Burdick. "Eccentricity Estimator for Wide-Angle Fovea Vision Sensor." Journal of Robotics and Mechatronics 21, no. 1 (2009): 128–34. http://dx.doi.org/10.20965/jrm.2009.p0128.

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This paper proposes a method for estimating the eccentricity that corresponds to the incident angle to a fovea sensor. The proposed method uses the Fourier-Mellin Invariant descriptor to estimate rotation, scale, and translation, by taking both geometrical distortion and non-uniform resolution of a space-variant image from the fovea sensor into account. The following 2 points are focused on in this paper. One is to use multi-resolution images by Discrete Wavelet Transform to properly reduce noise caused by foveation. Another is to use a variable window function (although the window function is

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19

Rajagopal, A. K. "Bivariate averaging functions, translation and scale autocorrelations, Fourier and Mellin transforms, the Wiener-Khinchine theorem and their inter-relationships." Pramana 38, no. 3 (1992): 233–47. http://dx.doi.org/10.1007/bf02875370.

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20

Elmasry, Amr, and Hosam Mahmoud. "Analysis of swaps in radix selection." Advances in Applied Probability 43, no. 2 (2011): 524–44. http://dx.doi.org/10.1239/aap/1308662491.

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Radix Sort is a sorting algorithm based on analyzing digital data. We study the number of swaps made by Radix Select (a one-sided version of Radix Sort) to find an element with a randomly selected rank. This kind of grand average provides a smoothing over all individual distributions for specific fixed-order statistics. We give an exact analysis for the grand mean and an asymptotic analysis for the grand variance, obtained by poissonization, the Mellin transform, and depoissonization. The digital data model considered is the Bernoulli(p). The distributions involved in the swaps experience a ph

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21

Elmasry, Amr, and Hosam Mahmoud. "Analysis of swaps in radix selection." Advances in Applied Probability 43, no. 02 (2011): 524–44. http://dx.doi.org/10.1017/s0001867800004973.

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Radix Sort is a sorting algorithm based on analyzing digital data. We study the number of swaps made by Radix Select (a one-sided version of Radix Sort) to find an element with a randomly selected rank. This kind of grand average provides a smoothing over all individual distributions for specific fixed-order statistics. We give an exact analysis for the grand mean and an asymptotic analysis for the grand variance, obtained by poissonization, the Mellin transform, and depoissonization. The digital data model considered is the Bernoulli(p). The distributions involved in the swaps experience a ph

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22

Butzer, P. L., and S. Jansche. "Mellin-Fourier series and the classical Mellin transform." Computers & Mathematics with Applications 40, no. 1 (2000): 49–62. http://dx.doi.org/10.1016/s0898-1221(00)00139-5.

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23

Twamley, J., and G. J. Milburn. "The quantum Mellin transform." New Journal of Physics 8, no. 12 (2006): 328. http://dx.doi.org/10.1088/1367-2630/8/12/328.

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24

YANG, JIANWEI, LIANG ZHANG, and ZHENGDA LU. "THE MELLIN CENTRAL PROJECTION TRANSFORM." ANZIAM Journal 58, no. 3-4 (2017): 256–64. http://dx.doi.org/10.1017/s1446181116000341.

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The central projection transform can be employed to extract invariant features by combining contour-based and region-based methods. However, the central projection transform only considers the accumulation of the pixels along the radial direction. Consequently, information along the radial direction is inevitably lost. In this paper, we propose the Mellin central projection transform to extract affine invariant features. The radial factor introduced by the Mellin transform, makes up for the loss of information along the radial direction by the central projection transform. The Mellin central p

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25

Čučković, Željko, and Bo Li. "Berezin Transform, Mellin Transform and Toeplitz Operators." Complex Analysis and Operator Theory 6, no. 1 (2010): 189–218. http://dx.doi.org/10.1007/s11785-010-0051-z.

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26

Yonggong Peng, Yixian Wang, Xiangwu Zuo, and Lihua Gong. "Properties of Fractional Mellin Transform." INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences 5, no. 5 (2013): 90–96. http://dx.doi.org/10.4156/aiss.vol5.issue5.11.

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27

Yang, Jianwei, Liang Zhang, and Zhengda Lu. "The Mellin central projection transform." ANZIAM Journal 58 (July 20, 2017): 256. http://dx.doi.org/10.21914/anziamj.v58i0.10980.

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28

Lamb, George, and O. P. Lossers. "Integral by Mellin Transform: 11067." American Mathematical Monthly 112, no. 9 (2005): 843. http://dx.doi.org/10.2307/30037618.

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29

Birmingham, D., and S. Sen. "A Mellin transform summation technique." Journal of Physics A: Mathematical and General 20, no. 13 (1987): 4557–60. http://dx.doi.org/10.1088/0305-4470/20/13/054.

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30

Venkataramanan, Lalitha, Fred K. Gruber, Tarek M. Habashy, and Denise E. Freed. "Mellin transform of CPMG data." Journal of Magnetic Resonance 206, no. 1 (2010): 20–31. http://dx.doi.org/10.1016/j.jmr.2010.05.015.

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31

Rogov, V. B. K. "The mellin-whittaker integral transform." Mathematical Notes of the Academy of Sciences of the USSR 39, no. 6 (1986): 434–37. http://dx.doi.org/10.1007/bf01157027.

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32

ZHENG SHI-HAI, CHEN YAN-SONG, and LI DE-HUA. "REALIZATION OF TWO-DIMENSIONAL MELLIN TRANSFORM." Acta Physica Sinica 39, no. 5 (1990): 749. http://dx.doi.org/10.7498/aps.39.749.

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33

Mohan, N. L., L. Anandababu, and S. V. Seshagiri Rao. "Gravity interpretation using the Mellin transform." GEOPHYSICS 51, no. 1 (1986): 114–22. http://dx.doi.org/10.1190/1.1442024.

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The Mellin transform of the gravity effect of a buried sphere and two‐dimensional horizontal circular cylinder, and the first horizontal derivative of the gravity effect of a two‐dimensional thin fault layer are derived. The transformed functions are bounded by two asymptotes. They are analyzed and procedures are formulated excluding the asymptotic regions for the extraction of the body parameters. The application of the Mellin transform is tested on simulated models as well as on two field examples: (1) the Humble Dome gravity anomaly near Houston, USA; and (2) the Louga gravity anomaly, USA.

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34

Kaiser, G. "Wavelet filtering with the Mellin transform." Applied Mathematics Letters 9, no. 5 (1996): 69–74. http://dx.doi.org/10.1016/0893-9659(96)00075-4.

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35

Fitouhi, A., N. Bettaibi, and K. Brahim. "The Mellin Transform in Quantum Calculus." Constructive Approximation 23, no. 3 (2005): 305–23. http://dx.doi.org/10.1007/s00365-005-0597-6.

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36

Passare, Mikael, and August Tsikh. "Residue Integrals and their Mellin Transforms." Canadian Journal of Mathematics 47, no. 5 (1995): 1037–50. http://dx.doi.org/10.4153/cjm-1995-055-4.

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AbstractGiven an almost arbitrary holomorphic map we study the structure of the associated residue integral and its Mellin transform, and the relation between these two objects. More precisely, we relate the limit behaviour of the residue integral to the polar structure of the Mellin transform. We consider also ideals connected to nonisolated singularities.

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37

Zhou, Zhibiao, Wei Xiao, and Yongshun Liang. "Partially Explore the Differences and Similarities between Riemann-Liouville Integral and Mellin Transform." Fractal and Fractional 6, no. 11 (2022): 638. http://dx.doi.org/10.3390/fractalfract6110638.

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At present many researchers devote themselves to studying the relationship between continuous fractal functions and their fractional integral. But little attention is paid to the relationship between Mellin transform and fractional integral. This paper aims to partially explore the differences and similarities between Riemann-Liouville integral and Mellin transform, then a 1-dimensional continuous and unbounded variational function defined on the closed interval [0,1] needs to be constructed. Through describing the image of the constructed function and its transformed function and proving the

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38

Yang, Jianwei, Liang Zhang, and Peiyao Li. "Radon–Fourier descriptor for invariant pattern recognition." International Journal of Wavelets, Multiresolution and Information Processing 17, no. 02 (2019): 1940004. http://dx.doi.org/10.1142/s0219691319400046.

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Radon transform is not only robust to noise, but also independent on the calculation of pattern centroid. In this paper, Radon–Mellin transform (RMT), which is a combination of Radon transform and Mellin transform, is proposed to extract invariant features. RMT converts any object into a closed curve. Radon–Fourier descriptor (RFD) is derived by applying Fourier descriptor to the obtained closed curve. The obtained RFD is invariant to scaling and rotation. (Generic) R-transform and some other Radon-based methods can be viewed as special cases of the proposed method. Experiments are conducted o

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39

A. S. Gudadhe, A. S. Gudadhe. "Abelian Theorem for Generalized Mellin-Whittaker Transform." IOSR Journal of Mathematics 1, no. 4 (2012): 19–23. http://dx.doi.org/10.9790/5728-0141923.

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40

Kiliçman, Adem. "A Note on Mellin Transform and Distributions." Mathematical and Computational Applications 9, no. 1 (2004): 65–72. http://dx.doi.org/10.3390/mca9010065.

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41

Deiermann, Paul, Cape Girardeau, Joseph Chalmers, and George L. Lamb. "An Application of the Mellin Transform: 10963." American Mathematical Monthly 111, no. 5 (2004): 441. http://dx.doi.org/10.2307/4145282.

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42

Al-Omari, S. K. Q., and Adem Kılıçman. "On Modified Mellin Transform of Generalized Functions." Abstract and Applied Analysis 2013 (2013): 1–6. http://dx.doi.org/10.1155/2013/539240.

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43

Rajan, Arvind, Melanie Po-Leen Ooi, Ye Chow Kuang, and Serge N. Demidenko. "Analytical Standard Uncertainty Evaluation Using Mellin Transform." IEEE Access 3 (2015): 209–22. http://dx.doi.org/10.1109/access.2015.2415592.

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44

Wu, C. Y., A. R. D. Somervell, T. G. Haskell, and T. H. Barnes. "Optical Mellin transform through Haar wavelet transformation." Optics Communications 227, no. 1-3 (2003): 75–82. http://dx.doi.org/10.1016/j.optcom.2003.09.040.

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45

Butzer, Paul L., and Stefan Jansche. "A direct approach to the mellin transform." Journal of Fourier Analysis and Applications 3, no. 4 (1997): 325–76. http://dx.doi.org/10.1007/bf02649101.

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46

Ilie, Mousa, Jafar Biazar, and Zainab Ayati. "Mellin transform and conformable fractional operator: applications." SeMA Journal 76, no. 2 (2018): 203–15. http://dx.doi.org/10.1007/s40324-018-0171-3.

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47

Ostrovsky, Dmitry. "Mellin Transform of the Limit Lognormal Distribution." Communications in Mathematical Physics 288, no. 1 (2009): 287–310. http://dx.doi.org/10.1007/s00220-009-0771-y.

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48

Prudnikov, A. P., Yu A. Brychkov, and O. I. Marichev. "Evaluation of integrals and the mellin transform." Journal of Soviet Mathematics 54, no. 6 (1991): 1239–341. http://dx.doi.org/10.1007/bf01373648.

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49

BRAHIM, Kamel, and Latifa RIAHI. "Two dimensional Mellin transform in Quantum Calculus." Acta Mathematica Scientia 38, no. 2 (2018): 546–60. http://dx.doi.org/10.1016/s0252-9602(18)30765-3.

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50

Alotta, Gioacchino, Mario Di Paola, and Giuseppe Failla. "A Mellin transform approach to wavelet analysis." Communications in Nonlinear Science and Numerical Simulation 28, no. 1-3 (2015): 175–93. http://dx.doi.org/10.1016/j.cnsns.2015.04.001.

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