Selective Extraction of Entangled Textures via Adaptive PDE Transform

Selective Extraction of Entangled Textures via Adaptive PDE Transform

Texture and feature extraction is an important research area with a wide range of applications in science and technology. Selective extraction of entangled textures is a challenging task due to spatial entanglement, orientation mixing, and high-frequency overlapping. The partial differential equation (PDE) transform is an efficient method for functional mode decomposition. The present work intr...

Image coding based on edges and textures via wavelet transform

The increasing interest on image compression is due to the increasing necessity of transmission velocity and memory to keep digital images, on many kind of midia. In order to reduce the quantity of bits needed to store images and, consequently, increase their transmission velocity, many coding methods have been studied, especially those which utilize transforms. This paper presents an image com...

Tempo Extraction via the Periodicity Transform

This short paper briefly describes an algorithm submitted for the MIREX 2005 tempo extraction contest. Key portions of the method are the feature vectors, a new method of resampling (a step required by the periodicity transform), and a modification to the periodicity transform that allows it to consider only periodicities within some prespecified range. The strengths and weaknesses of the algor...

Document Annotation via Adaptive Information Extraction

Biomolecular surface construction by PDE transform.

This work proposes a new framework for the surface generation based on the partial differential equation (PDE) transform. The PDE transform has recently been introduced as a general approach for the mode decomposition of images, signals, and data. It relies on the use of arbitrarily high-order PDEs to achieve the time-frequency localization, control the spectral distribution, and regulate the s...