Abstract: In recent times the spatial autoregressive models have been extensively used to represent images. In this paper we propose an algorithm to represent and reproduce texture images based on the estimation of spatial autoregressive processes. The image intensity is locally modeled by a first spatial autoregressive model with support in a strongly causal prediction region on the plane. A basic criteria to quantify similarity between two images is used to locally select this region among four different possibilities, corresponding to the four strongly causal regions on the plane. Two global image similarity measures are used to evaluate the performance of our proposal.

Silvia María Ojeda and Grisel Maribel Britos, “A New Algorithm to Represent Texture Images” International Journal of Advanced Computer Science and Applications(IJACSA), 4(6), 2013. http://dx.doi.org/10.14569/IJACSA.2013.040614

@article{Ojeda2013,
title = {A New Algorithm to Represent Texture Images},
journal = {International Journal of Advanced Computer Science and Applications}
doi = {10.14569/IJACSA.2013.040614},
url = {http://dx.doi.org/10.14569/IJACSA.2013.040614},
year = {2013},
publisher = {The Science and Information Organization},
volume = {4},
number = {6},
author = {Silvia María Ojeda and Grisel Maribel Britos},
}