We propose a discrete regularization framework on weighted graphs of arbitrary topology, which unifies image and mesh filtering. The approach considers the problem as a variation...
We consider the estimation of an unknown arbitrary 2D object shape from sparse noisy samples of its Fourier transform. The estimate of the closed boundarycurve is parametrized by ...
In this paper we describe a new method for improving the representation of textures in blends of multiple images based on a Markov Random Field (MRF) algorithm. We show that direc...
We propose a block-based transform optimization and associated image compression technique that exploits regularity along directional image singularities. Unlike established work,...
Osman Gokhan Sezer, Oztan Harmanci, Onur G. Gulery...
In this paper, we introduce a rotational invariant feature set for texture segmentation and classification, based on an extension of fractal dimension (FD) features. The FD extract...