Multiscale singularity trees

Multi-Scale Singularity Trees (MSSTs)

Transitions of Multi-scale Singularity Trees

Multi-Scale Singularity Trees (MSSTs) are multi-scale image descriptors aimed at representing the deep structures of images [2]. Changes in images are directly translated to changes in the deep structures; therefore transitions in MSSTs. Because MSSTs can be used to represent the deep structure of images efficiently, it is important to investigate and understand their transitions and impacts. W...

Fractal estimation using models on multiscale trees

In this paper we estimate the fractal dimension of stochastic processes with 1/f-like spectra by applying a recently-introduced multiresolution framework. This framework admits an efficient likelihood function evaluation, allowing us to compute the maximum likelihood estimate of this fractal parameter with relative ease. In addition to yielding results that compare well to other proposed method...

Fiedler trees for multiscale surface analysis

In this work we introduce a new hierarchical surface decomposition method for multiscale analysis of surface meshes. In contrast to other multiresolution methods, our approach relies on spectral properties of the surface to build a binary hierarchical decomposition. Namely, we utilize the first nontrivial eigenfunction of the Laplace-Beltrami operator to recursively decompose the surface. For t...

Multi-scale Singularity Trees: Soft-Linked Scale-Space Hierarchies