In this paper we propose a novel error concealment algorithm for block-based video transmission over errorprone networks. In particular, we develop a spatial error concealment technique which combines edge-preserving interpolation and texture analysis and synthesis, providing a reconstruction of lost macroblocks optimized for visual perception. In particular, the algorithm recovers image edges ...

We present a user-centered approach to image-based texture synthesis. The synthesis uses a user-defined brush as generation primitive. This allows synthesis of textures at the texel level and further integration of the method into most of the existing digital image edition softwares. We treat texture images as probability density estimators from which new images with perceptually similar appear...

This paper describes the basic steps of a new technique, called bunch sampling, that enables the realistic synthesis of spatially homogeneous textures. A geometric shape of the bunch (acting as a texel) and spatial placement grid governing relative positions of the bunches are estimated from the training texture by using a generic Gibbs random field texture model with multiple pairwise pixel in...

A novel approach for coding textured images is presented. The texture field is assumed to be a realization of a regular homogeneous random field, which can have a mixed spectral distribution. On the basis of a two-dimensional (2-D) Wold-like decomposition, the field is represented as a sum of a purely indeterministic, harmonic, and countable number of evanescent fields. We present an algorithm ...

An unsupervised multiresolution conditional random field (CRF) approach to texture segmentation problems is introduced. This approach involves local and long-range information in the CRF neighbourhood to determine the classes of image blocks. Like most Markov random field (MRF) approaches, the proposed method treats the image as an array of random variables and attempts to assign an optimal cla...

The goal of this thesis is to build a computational system that is able to identify object categories within images. To this end, this thesis proposes a computational model of “recognition-through-decomposition-and-fusion” based on the psychophysical theories of information dissociation and integration in human visual perception. At the lowest level, contour and texture processes are defined an...

The task of texture classification is to determine the category of a texture image. Most texture classifiers have been trained on a training set of positive and negative examples, with purpose to learn to separate the positives from the negatives. The possible negatives are usually unlimited. The performance and accuracy of texture classifiers therefore largely depend on the choice of negatives...

Psychophysical and fMRI studies have indicated that visual processing of global symmetry has distinctive scaling properties, and proceeds more slowly than analysis of contrast, spatial frequency, and texture. We therefore undertook a visual evoked potential (VEP) study to directly compare the dynamics of symmetry and texture processing, and to determine the extent to which they interact. Stimul...

Electrical steels are important alloys widely used in electrical instruments. The magnetic properties and low core loss of grain oriented silicon steels are closely related to the sharpness of Goss texture ({110} ).The direction of is the softest direction for magnetism.  In this work, the microstructure and dependence of orientation density along the major texture fibers on the applied cold ro...

The TEXRET-System, a texture retrieval system based on soft-computing technologies is being developed. One of the main system features is synthesis of the requested textures when these are not found in the database, which allows a growing of the database. Missing textures are synthesized interactively using Markov Random Fields and interactive genetic algorithms. This article is centered on the...