Titlebook: Mathematical Methods in Time Series Analysis and Digital Image Processing; Rainer Dahlhaus,Jürgen Kurths,Jens Timmer Book 2008 Springer-Ve

aspect

Book 2008ical engineering, theoretical physics, mathematics and the computer sciences. ..In particular, mathematically justified algorithms and methods, the mathematical analysis of these algorithms, and methods as well as the investigation of connections between methods from time series analysis and image p

Pandemic

Book 2008ronmental sciences, is also addressed...This volume coherently summarizes work carried out in the field of theoretical signal and image processing. It focuses on non-linear and non-parametric models for time series as well as on adaptive methods in image processing..

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Multiscale Approximation, respect, wavelet methods offer an alternative to classical Fourier- or Gabortransforms which create a phase space consisting of a time/space- frequency parametrization. Hence, wavelet methods are advantageous whenever local, non-stationary structures on different scales have to be analyzed.

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Multiscale Approximation,ccess of wavelet methods is based on their potential for resolving local properties and to analyze non-stationary structures. This is achieved by multiscale decompositions, e.g., a signal or image is mapped to a phase space parametrized by a time/space- and a scale/size/resolution parameter. In this

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Inverse Problems and Parameter Identification in Image Processing, actual image acquisition are usually not known. Examples for this are the inhomogeneities of the magnetic field in magnetic resonance imaging (MRI) leading to nonlinear deformations of the anatomic structures in the recorded images, material parameters in geological structures as unknown parameters