This thesis investigates texture classification using Non-Parametric Markov Random fields. Texture models using local image descriptors are investigated. Classification performance using such models is then reported upon and the results are used to guide development of future classifiers which take account of scale information within an image. The issues and effects of scale within texture mode...

Texture remains largely underutilized in the analysis of remote sensed datasets compared to descriptors based on the orthogonal spectral dimension. This paper describes our recent efforts towards using texture to automate the annotation of remote sensed imagery Two applications are described that use the homogeneous texture descriptor recently standardized by MPEG-7. In the Jirst, higher-level ...

Texture is an important part of the visual world of animals and men and their visual systems successfully detect, discriminate and segment texture. Relatively recently progress was made concerning structures in the brain which are presumably responsible for texture processing. Von der Heydt et al. (von der Heydt et al. 1992) reported on the discovery of a texture processing neuron in areas V1 a...

This article presents a mathematical de nition of texture { the Julesz ensemble (h), which is the set of all images (de ned on Z) that share identical statistics h. Then texture modeling is posed as an inverse problem: given a set of images sampled from an unknown Julesz ensemble (h ), we search for the statistics h which de ne the ensemble. A Julesz ensemble (h) has an associated probability d...

Gaussian cosmological models, typified by the inflationary cold dark matter models, and non-Gaussian topological defect based cosmological models, such as the texture seeded model, differ in the origin of large-scale cosmic structures. In the former it is believed that peaks at appropriate scales in the initial high density field are the sites onto which matter accretes and collapses to form th...

Inpainting consists in computing a plausible completion of missing parts of an image 4 given the available content. In the restricted framework of texture images, the image can be seen as a 5 realization of a random field model, which gives a stochastic formulation of image inpainting: on the 6 masked exemplar one estimates a random texture model which can then be conditionally sampled in 7 ord...

The Bidirectional Texture Function (BTF) is the recent most advanced representation of visual properties of surface materials. It specifies their appearance due to varying spatial, illumination, and viewing conditions. Corresponding enormous BTF measurements require a mathematical representation allowing extreme compression but simultaneously preserving its high visual fidelity. We present a no...

Texture models are widely in use for image content description. In remote-sensing images textures occur at very different scales, requiring the application of several texture models. This paper presents a scale selection algorithm based on a multi-scale random field model with a dynamic pyramidal structure. The algorithm returns the scales and the regions where texture is present. It is designe...

This paper aims to improve the accuracy of texture classification based on extracting texture features using five different texture methods and classifying the patterns using a naïve Bayesian classifier. Three statistical-based and two model-based methods are used to extract texture features from eight different texture images, then their accuracy is ranked after using each method individually ...