Modeling textures using Gaussian Markov random fields (GMRF) has been successfully used in classifying textures. However, these models do not perform well for self-similar textures such as those generated from fractional Brownian motion. The authors show that by using the difference images at different scales instead of the original image, one can significantly increase the performance of classifying self-similar texture patterns using GMRF models.<>
Multi-resolution texture analysis of self-similar textures using hierarchical Gaussian Markov random field models
Proceedings of 1st International Conference on Image Processing ; 3 ; 417-420 vol.3
1994-01-01
303460 byte
Conference paper
Electronic Resource
English
British Library Conference Proceedings | 1994
|Infrared Texture Simulation Using Gaussian-Markov Random Fields
British Library Online Contents | 2004
|Gaussian Markov random field based improved texture descriptor for image segmentation
British Library Online Contents | 2014
|Texture analysis using partially ordered Markov models
IEEE | 1994
|Texture Analysis using Partially Ordered Markov Models
British Library Conference Proceedings | 1994
|