We present a universal statistical model for texture images in the context of an over-complete complex wavelet transform. The model is parameterized by a set of statistics computed on pairs of coeecients corresponding to basis functions at adjacent spatial locations , orientations, and scales. We develop an eecient algorithm for synthesizing random images subject to these constraints, by iterat...

Traditionally, human texture perception has been studied using artificial textures made of random-dot patterns or abstract structured elements. At the same time, computer algorithms for the synthesis of natural textures have improved dramatically. The current study seeks to unify these two fields of research through a psychophysical assessment of a particular computational model, thus providing...

In this paper, a texture classification method based on multi-model feature integration by Bayesian networks is proposed. Considering that many image textures exhibit both structural and statistical properties, two feature sets based on two texture models––the Gabor model and the Gaussian Markov random field model are used to describe the image properties in both structure and statistics. A Bay...

This paper presents a novel texture descriptor based on the wavelet transform. First, we will consider vertical and horizontal coefficients at the same position as the components of a bivariate random vector. The magnitud and angle of these vectors are computed and its histograms are analyzed. This empirical magnitud histogram is modelled by using a gamma distribution (pdf). As a result, the fe...

Exemplar-based texture synthesis is the process of generating, from an input sample, new texture images of arbitrary size and which are perceptually equivalent to the sample. The two main approaches are statisticsbased methods and patch re-arrangement methods. In the first class, a texture is characterized by a statistical signature; then, a random sampling conditioned to this signature produce...

Texture is one of the most important features for object detection and recognition. In many applications, it is derived from the responses of texture filters. In this paper, we evaluate the potential of seven texture filter banks for the pixel-based classification of terrestrial facade images. Particularly, we analyze features from Gabor, Haar, Root Filter Set, and Walsh filters as well as filt...