Two new parameters for the ordinal analysis of images

TL;DR

This paper introduces two new parameters based on 2x2 pixel patterns that effectively characterize and differentiate textures in images, especially isotropic structures, enhancing image analysis techniques.

Contribution

It identifies three types of 2x2 pixel patterns and proposes two parameters derived from their statistics to improve texture classification.

Findings

Parameters are most stable for isotropic textures

Parameters effectively distinguish different textures

Enhances statistical tools for image analysis

Abstract

Local patterns play an important role in statistical physics as well as in image processing. Two-dimensional ordinal patterns were studied by Ribeiro et al. who determined permutation entropy and complexity in order to classify paintings and images of liquid crystals. Here we find that the 2 by 2 patterns of neighboring pixels come in three types. The statistics of these types, expressed by two parameters, contains the relevant information to describe and distinguish textures. The parameters are most stable and informative for isotropic structures.