Searching for image information content, its discovery, extraction, and representation

TL;DR

This paper introduces a new definition of image information content based on Kolmogorov complexity, proposing a multi-level description framework and an algorithm for extracting image data structures.

Contribution

It presents a novel theoretical framework for defining and describing image information content, along with an algorithm for creating such descriptors.

Findings

The proposed method effectively describes image structures at multiple levels.

Examples demonstrate the algorithm's capability to generate meaningful image descriptors.

The approach offers a new perspective on image information content analysis.

Abstract

Image information content is known to be a complicated and controvercial problem. This paper posits a new image information content definition. Following the theory of Solomonoff-Kolmogorov-Chaitin's complexity, we define image information content as a set of descriptions of imafe data structures. Three levels of such description can be generally distinguished: 1)the global level, where the coarse structure of the entire scene is initially outlined; 2) the intermediate level, where structures of separate, non-overlapping image regions usually associated with individual scene objects are deliniated; and 3) the low-level description, where local image structures observed in a limited and restricted field of view are resolved. A technique for creating such image information content descriptors is developed. Its algorithm is presented and elucidated with some examples, which demonstrate the effectiveness of the proposed approach.