Self-Similar Prior and Wavelet Bases for Hidden Incompressible Turbulent Motion

Self-Similar Prior and Wavelet Bases for Hidden Incompressible Turbulent Motion

This work is concerned with the ill-posed inverse problem of estimating turbulent flows from the observation of an image sequence. From a Bayesian perspective, a divergence-free isotropic fractional Brownian motion (fBm) is chosen as a prior model for instantaneous turbulent velocity fields. This self-similar prior characterizes accurately second-order statistics of velocity fields in incompres...

Self-similar regularization of optic-flow for turbulent motion estimation

Based on self-similar models of turbulence, we propose in this paper a multi-scale regularizer in order to provide a closure to the optic-flow estimation problem. Regularization is achieved by constraining motion increments to behave as a self-similar process. The associate constrained minimization problem results in a collection of first-order optic-flow regularizers acting at the different sc...

The Self - Similar Turbulent Dynamo

We consider the problem of magnetic-energy amplification by a turbulent flow of conducting fluid. This effect is known as the small-scale turbulent dynamo, and it is believed to be relevant in application to magnetic fields in astrophysical objects. It is, in fact, a generic property of random (in time and/or space) flows that they can amplify magnetic fluctuations at scales smaller than the sc...

Mathematical models of turbulent motion of an incompressible viscous fluid

Wavelet-based self-similar watermarking for still images

This paper presents a wavelet-based watermarking method for copyright protection of still images. Watermarks are structured in such a way to attain spatial self-similarity with respect to a cartesian grid. Embedding and detection are performed in the wavelet domain allowing thus multiresolution detection. The novelty of the current approach is the use of self-similar watermarks (quasi scaleinva...