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We study the use of the quantum wavelet transform to extract efficiently information about the multifractal exponents for multifractal quantum states. We show that, combined with quantum simulation algorithms, it enables to build quantum…

Quantum Physics · Physics 2009-09-24 I. Garcia-Mata , O. Giraud , B. Georgeot

While there is an increasing amount of literature about Bayesian time series analysis, only a few Bayesian nonparametric approaches to multivariate time series exist. Most methods rely on Whittle's Likelihood, involving the second order…

Methodology · Statistics 2018-11-27 Alexander Meier , Claudia Kirch , Renate Meyer

Multi-scale decomposition has been an invaluable tool for the processing of physiological signals. Much focus in multi-scale decomposition for processing such signals have been based on scale-space theory and wavelet transforms. In this…

Methodology · Statistics 2015-06-03 Alexander Wong , Xiao Yu Wang

In this paper, we consider nonparametric multidimensional finite mixture models and we are interested in the semiparametric estimation of the population weights. Here, the i.i.d. observations are assumed to have at least three components…

Statistics Theory · Mathematics 2017-12-14 Elisabeth Gassiat , Judith Rousseau , Elodie Vernet

Texture classification is an active topic in image processing which plays an important role in many applications such as image retrieval, inspection systems, face recognition, medical image processing, etc. There are many approaches…

Computer Vision and Pattern Recognition · Computer Science 2018-04-03 Shervan Fekri-Ershad

Differentiable rendering aims to compute the derivative of the image rendering function with respect to the rendering parameters. This paper presents a novel algorithm for 6-DoF pose estimation through gradient-based optimization using a…

Computer Vision and Pattern Recognition · Computer Science 2022-12-27 Ramchander Rao Bhaskara , Roshan Thomas Eapen , Manoranjan Majji

We consider the semi-parametric estimation of a scale parameter of a one-dimensional Gaussian process with known smoothness. We suggest an estimator based on quadratic variations and on the moment method. We provide asymptotic…

Statistics Theory · Mathematics 2020-01-22 Jean-Marc Azaïs , François Bachoc , Agnès Lagnoux , Thi Mong Ngoc Nguyen

The quantitative phase image formation process is posed as a problem of parameter estimation from intensity measurements. This approach is inclusive of traditional pixel-oriented imaging, where the sought parameters are the pixel values.…

Classical Physics · Physics 2024-07-04 George Barbastathis

Mesh deformation plays a pivotal role in many 3D vision tasks including dynamic simulations, rendering, and reconstruction. However, defining an efficient discrepancy between predicted and target meshes remains an open problem. A prevalent…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Tung Le , Khai Nguyen , Shanlin Sun , Kun Han , Nhat Ho , Xiaohui Xie

We generalize the wavelet transform modulus maxima (WTMM) method to multifractal analysis of 3D random fields. This method is calibrated on synthetic 3D monofractal fractional Brownian fields and on 3D multifractal singular cascade measures…

Statistical Mechanics · Physics 2009-11-10 Pierre Kestener , Alain Arneodo

The Easy Path Wavelet Transform is an adaptive transform for bivariate functions (in particular natural images) which has been proposed in [1]. It provides a sparse representation by finding a path in the domain of the function leveraging…

Information Theory · Computer Science 2017-02-16 Renato Budinich

In the usual Bayesian setting, a full probabilistic model is required to link the data and parameters, and the form of this model and the inference and prediction mechanisms are specified via de Finetti's representation. In general, such a…

Methodology · Statistics 2026-01-21 Yu Luo , David A. Stephens , Daniel J. Graham , Emma J. McCoy

The Dirichlet distribution, also known as multivariate beta, is the most used to analyse frequencies or proportions data. Maximum likelihood is widespread for estimation of Dirichlet's parameters. However, for small sample sizes, the…

Methodology · Statistics 2021-03-04 Vincenzo Gioia , Euloge Clovis Kenne Pagui

This paper is concerned with the numerical solution of model-based, Bayesian inverse problems. We are particularly interested in cases where the cost of each likelihood evaluation (forward-model call) is expensive and the number of un-…

Computation · Statistics 2016-07-25 Isabell M. Franck , P. S. Koutsourelakis

Measured Bidirectional Texture Function (BTF) can faithfully reproduce a realistic appearance but is costly to acquire and store due to its 6D nature (2D spatial and 4D angular). Therefore, it is practical and necessary for rendering to…

Graphics · Computer Science 2024-05-24 Zilin Xu , Zahra Montazeri , Beibei Wang , Ling-Qi Yan

Modern imaging techniques heavily rely on Bayesian statistical models to address difficult image reconstruction and restoration tasks. This paper addresses the objective evaluation of such models in settings where ground truth is…

Image and Video Processing · Electrical Eng. & Systems 2026-05-29 Tom Sprunck , Marcelo Pereyra , Tobias Liaudat

Recent developments in image quality, data storage, and computational capacity have heightened the need for texture analysis in image process. To date various methods have been developed and introduced for assessing textures in images. One…

Computer Vision and Pattern Recognition · Computer Science 2014-06-30 Omer Faruk Ertugrul

While multislice electron ptychography can provide thermal-vibration limited resolution and 3D information, it relies on the proper selection of many intertwined experimental and computational parameters. Here, we outline a theoretical…

Materials Science · Physics 2023-11-28 Colin Gilgenbach , Xi Chen , James M. LeBeau

Bayesian image analysis has played a large role over the last 40+ years in solving problems in image noise-reduction, de-blurring, feature enhancement, and object detection. However, these problems can be complex and lead to computational…

Methodology · Statistics 2024-01-15 John Kornak , Karl Young , Eric Friedman

Computer vision tasks are difficult because of the large variability in the data that is induced by changes in light, background, partial occlusion as well as the varying pose, texture, and shape of objects. Generative approaches to…

Computer Vision and Pattern Recognition · Computer Science 2018-11-30 Adam Kortylewski , Mario Wieser , Andreas Morel-Forster , Aleksander Wieczorek , Sonali Parbhoo , Volker Roth , Thomas Vetter
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