Sciweavers

Share
SCALESPACE
2015
Springer

Multiscale Texture Orientation Analysis Using Spectral Total-Variation Decomposition

3 years 4 months ago
Multiscale Texture Orientation Analysis Using Spectral Total-Variation Decomposition
Abstract. Multi-level texture separation can considerably improve texture analysis, a significant component in many computer vision tasks. This paper aims at obtaining precise local texture orientations of images in a multiscale manner, characterizing the main obvious ones as well as the very subtle ones. We use the total variation spectral framework to decompose the image into its different textural scales. Gabor filter banks are then employed to detect prominent orientations within the multiscale representation. A necessary condition for perfect texture separation is given, based on the spectral total-variation theory. We show that using this method we can detect and differentiate a mixture of overlapping textures and obtain with high fidelity a multi-valued orientation representation of the image.
Dikla Horesh, Guy Gilboa
Added 17 Apr 2016
Updated 17 Apr 2016
Type Journal
Year 2015
Where SCALESPACE
Authors Dikla Horesh, Guy Gilboa
Comments (0)
books