Results 1 - 10 of 8,364

A Parametric Texture Model based on Joint Statistics of Complex Wavelet Coefficients

by Javier Portilla, Eero P. Simoncelli - INTERNATIONAL JOURNAL OF COMPUTER VISION , 2000
"... We present a universal statistical model for texture images in the context of an overcomplete complex wavelet transform. The model is parameterized by a set of statistics computed on pairs of coefficients corresponding to basis functions at adjacent spatial locations, orientations, and scales. We de ..."
Abstract - Cited by 424 (13 self) - Add to MetaCart
We present a universal statistical model for texture images in the context of an overcomplete complex wavelet transform. The model is parameterized by a set of statistics computed on pairs of coefficients corresponding to basis functions at adjacent spatial locations, orientations, and scales. We

Temporal Texture Modeling

by Martin Szummer, Rosalind W. Picard - In IEEE International Conference on Image Processing , 1996
"... Temporal textures are textures with motion. Examples include wavy water, rising steam and fire. We model image sequences of temporal textures using the spatio-temporal autoregressive model (STAR). This model expresses each pixel as a linear combination of surrounding pixels lagged both in space and ..."
Abstract - Cited by 147 (1 self) - Add to MetaCart
Temporal textures are textures with motion. Examples include wavy water, rising steam and fire. We model image sequences of temporal textures using the spatio-temporal autoregressive model (STAR). This model expresses each pixel as a linear combination of surrounding pixels lagged both in space

Minimax Entropy Principle and Its Application to Texture Modeling

by Song Chun Zhu, Ying Nian Wu, David Mumford , 1997
"... This article proposes a general theory and methodology, called the minimax entropy principle, for building statistical models for images (or signals) in a variety of applications. This principle consists of two parts. The first is the maximum entropy principle for feature binding (or fusion): for a ..."
Abstract - Cited by 224 (46 self) - Add to MetaCart
because of the sample variation in the observed feature statistics. The minimax entropy principle is applied to texture modeling, where a novel Markov random field (MRF) model, called FRAME (Filter, Random field, And Minimax Entropy), is derived, and encouraging results are obtained in experiments on a

Reflectance and texture of real-world surfaces

by Kristin J. Dana, Bram van Ginneken, Shree K. Nayar, Jan J. Koenderink - ACM TRANS. GRAPHICS , 1999
"... In this work, we investigate the visual appearance of real-world surfaces and the dependence of appearance on scale, viewing direction and illumination direction. At ne scale, surface variations cause local intensity variation or image texture. The appearance of this texture depends on both illumina ..."
Abstract - Cited by 590 (23 self) - Add to MetaCart
In this work, we investigate the visual appearance of real-world surfaces and the dependence of appearance on scale, viewing direction and illumination direction. At ne scale, surface variations cause local intensity variation or image texture. The appearance of this texture depends on both

Fast texture synthesis using tree-structured vector quantization

by Li-yi Wei, Marc Levoy , 2000
"... Figure 1: Our texture generation process takes an example texture patch (left) and a random noise (middle) as input, and modifies this random noise to make it look like the given example texture. The synthesized texture (right) can be of arbitrary size, and is perceived as very similar to the given ..."
Abstract - Cited by 561 (12 self) - Add to MetaCart
Field texture models and generates textures through a deterministic searching process. We accelerate this synthesis process using tree-structured vector quantization.

Pyramid-Based Texture Analysis/Synthesis

by David J. Heeger, James R. Bergen , 1995
"... This paper describes a method for synthesizing images that match the texture appearanceof a given digitized sample. This synthesis is completely automatic and requires only the "target" texture as input. It allows generation of as much texture as desired so that any object can be covered. ..."
Abstract - Cited by 480 (0 self) - Add to MetaCart
. It can be used to produce solid textures for creating textured 3-d objects without the distortions inherent in texture mapping. It can also be used to synthesize texture mixtures, images that look a bit like each of several digitized samples. The approach is based on a model of human texture perception

Selecting Scales for Texture Models

by Hubert Rehrauer - Machine Perception & Artificial Intelligence. World Scientific , 2000
"... 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 st ..."
Abstract - Cited by 1 (1 self) - Add to MetaCart
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

Learning to detect natural image boundaries using local brightness, color, and texture cues

by David R. Martin, Charless C. Fowlkes, Jitendra Malik - PAMI , 2004
"... The goal of this work is to accurately detect and localize boundaries in natural scenes using local image measurements. We formulate features that respond to characteristic changes in brightness, color, and texture associated with natural boundaries. In order to combine the information from these fe ..."
Abstract - Cited by 625 (18 self) - Add to MetaCart
outperforms existing approaches. Our two main results are 1) that cue combination can be performed adequately with a simple linear model and 2) that a proper, explicit treatment of texture is required to detect boundaries in natural images.

Feature selection: Evaluation, application, and small sample performance

by Anil Jain, Douglas Zongker - IEEE Transactions on Pattern Analysis and Machine Intelligence , 1997
"... Abstract—A large number of algorithms have been proposed for feature subset selection. Our experimental results show that the sequential forward floating selection (SFFS) algorithm, proposed by Pudil et al., dominates the other algorithms tested. We study the problem of choosing an optimal feature s ..."
Abstract - Cited by 474 (13 self) - Add to MetaCart
set for land use classification based on SAR satellite images using four different texture models. Pooling features derived from different texture models, followed by a feature selection results in a substantial improvement in the classification accuracy. We also illustrate the dangers of using

Multiview Texture Models

by Alexey Zalesny, Luc Van Gool , 2001
"... Mapping textured images on smoothly approximated surfaces is often used to conceal the loss of their real, fine-grained relief. A limitation of mapping a fixed texture in such cases is that it will only be correct for one viewing and one illumination direction. The presence of geometric surface deta ..."
Abstract - Cited by 15 (1 self) - Add to MetaCart
details causes changes that simple foreshortening and global color scaling cannot model well. Hence, one would like to synthesize different textures for different viewing conditions. A texture model is presented that takes account of viewpoint dependent changes in texture appearance. It is highly compact
Results 1 - 10 of 8,364