Image compression by means of the multidimensional circulant covariance extension problem -- Revisited

TL;DR

This paper revisits image compression using a multidimensional circulant covariance extension framework, exploring new objective functions and prior designs to improve compression paradigms.

Contribution

It introduces refined compression methods by considering alternative objective functions and prior designs within the circulant covariance extension framework.

Findings

Enhanced image compression paradigms

Flexible design of priors and objectives

Potential for improved compression quality

Abstract

We revisit the image compression problem using the framework introduced by Ringh, Karlsson and Lindquist. More precisely, we explore the possibility to consider a family of objective functions and a different way to design the prior in the corresponding multidimensional circulant covariance extension problem. The latter leads to refined compression paradigms.