What question did this study set out to answer?

To summarize the contributions of Eugène Pechersky to image processing, particularly through Bayesian methods and model development.

April 25, 2026Markov Processes And Related Fields0 citations

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When Statistical Physics Meets Image Processing

XDX. DescombesInstitut national de recherche en sciences et technologies du numérique MSM. SigelleTélécom Paris FTF. TupinTélécom Paris

Key Points

To summarize the contributions of Eugène Pechersky to image processing, particularly through Bayesian methods and model development.
Reviewed Pechersky's work during his time at Telecom Paris and INRIA Sophia Antipolis.
Analyzed multi-body interaction models designed to enhance traditional image processing techniques.
Examined applications of the derived models in remote sensing and biomedical imaging.
Developed models that extend the traditional Ising and Potts models for specific image processing tasks.
Identified successful applications of these models in remote sensing and biomedical images, highlighting their effectiveness.
Emphasized the role of Bayesian approaches in bridging statistical physics and image processing.

Abstract

In this paper we review the contribution of Evgueny (Eugène for the French community) Pechersky to image processing. Eugène discovered image processing as he was visiting Telecom Paris in 1994. During his stay at Telecom Paris and later on, during some visits and collaboration at INRIA Sophia Antipolis, his work was focused on designing multi-body interaction models to overcome the limits of the well known Ising and Potts model for image processing applications. Notably, the derived models were applied to different applications both in remote sensing and biomedical images. In this paper we summarize Eugène's contribution to the so-called Bayesian approach in image processing.

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When Statistical Physics Meets Image Processing

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