Three-dimensional maps are fundamental tools for presenting, exploring, and manipulating geo data. This paper describes multiresolution concepts for 3D maps and their texture-based design. In our approach, 3D maps are based on a hybrid, multiresolution terrain model composed of data sets having different topological structure, for example a coarse regular grid combined with by triangulated micr...

Application of the Minimum Description Length (MDL) principle to multiresolution image denoising has been somewhat unsuccessful to date. This disappointing performance is due to the crudeness of the underlying prior image models, which lead to overly sparse solutions. We propose a new family of complexity priors based on Rissanen's universal prior for integers , which produces estimates with be...

Despite being routinely required in medical applications, deformable surface registration is notoriously difficult due to large intersubject variability and complex geometry of most medical datasets. We present a general and flexible deformable matching framework based on generalized surface flows that efficiently tackles these issues through tailored deformation priors and multiresolution comp...

We propose a modification of the generalized gradient vector flow field techniques based on multiresolution analysis and phase portrait techniques. The original image is subjected to mutliresolutional analysis to create a sequence of approximation and detail images. The approximations are converted into an edge map and subsequently into a gradient field subjected to the generalized gradient vec...

The performances of many image analysis tasks depend on the image resolution at which they are applied. Traditionally, resolution selection methods rely on spatial derivatives of image intensities. Differential measurements, however, are sensitive to noise and are local. They cannot characterize patterns, such as textures, which are defined over extensive image regions. In this work, we present...

In this paper, we investigate various connections between wavelet shrinkage methods in image processing and Bayesian estimation using Generalized Gaus-sian priors. We present fundamental properties of the shrinkage rules implied by Generalized Gaussian and other heavy{tailed priors. This allows us to show a simple relationship between diierentiability of the log{ prior at zero and the sparsity ...

The recent increase in the generated polygonal dataset sizes has outpaced the performance of graphics hardware. Several solutions such as multiresolution hierarchies and level-of-detail rendering have been developed to bridge the increasing gap. However, the discrete levels of detail generate annoying popping effects, the preliminaries multiresolution schemes cannot perform drastic changes on t...

We present a functional framework for the design of tight steerable wavelet frames in any number of dimensions. The 2-D version of the method can be viewed as a generalization of Simoncelli’s steerable pyramid that gives access to a larger palette of steerable wavelets via a suitable parametrization. The backbone of our construction is a primal isotropic wavelet frame that provides the multires...

Multiresolution tree-structured models are attractive when dealing with large amounts of spatial data in environmental sciences. With the multiresolution tree structure, a change-of-resolution Kalman filter algorithm has been devised to predict spatial processes in a computationally efficient manner (see, e.g., Huang and Cressie (1997) and Huang, Cressie and Gabrosek (2002)). In this article, w...