35.4: Random Field Texture Coding

نویسنده

  • Rosalind W. Picard
چکیده

Random eld models are able to synthesize a large variety of complex patterns with a small number of parameters. This paper discusses the use of a Gibbs random eld model as part of an image coding system. In particular, some semantic and perceptual attributes of this model are addressed.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Primal sketch: Integrating structure and texture

This article proposes a generative image model, which is called “primal sketch,” following Marr’s insight and terminology. This model combines two prominent classes of generative models, namely, sparse coding model and Markov random field model, for representing geometric structures and stochastic textures respectively. Specifically, the image lattice is divided into structure domain and textur...

متن کامل

Texture coding using a Wold decomposition model

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 ...

متن کامل

Primal sketch : Integrating structure and texture q

This article proposes a generative image model, which is called ‘‘primal sketch,’’ following Marr’s insight and terminology. This model combines two prominent classes of generative models, namely, sparse coding model and Markov random field model, for representing geometric structures and stochastic textures, respectively. Specifically, the image lattice is divided into structure domain and tex...

متن کامل

A Compound Moving Average Bidirectional Texture Function Model

This paper describes a simple novel compound random field model capable of realistic modelling the most advanced recent representation of visual properties of surface materials the bidirectional texture function. The presented compound random field model combines a non-parametric control random field with local multispectral models for single regions and thus allows to avoid demanding iterative...

متن کامل

Vector field visualization using Markov Random Field texture synthesis

Vector field visualization generates an image to convey the information existing in the data. We use Markov Random Field texture synthesis methods to generate the visualization from a set of example textures. The examples textures are chosen according to the vector data for each pixel of the output. This leads to dense visualizations with arbitrary example textures.

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1992