Image Dynamic Range Enhancement in the Context of Logarithmic Models

TL;DR

This paper explores logarithmic models for images to enhance their dynamic range, proposing two transforms for optimal enhancement and demonstrating their effectiveness through experiments.

Contribution

It introduces two novel image transforms within logarithmic models for dynamic range enhancement, addressing the challenge of variable illumination conditions.

Findings

Effective dynamic range enhancement demonstrated

Transforms improve image visibility under different lighting

Experimental results validate the proposed methods

Abstract

Images of a scene observed under a variable illumination or with a variable optical aperture are not identical. Does a privileged representant exist? In which mathematical context? How to obtain it? The authors answer to such questions in the context of logarithmic models for images. After a short presentation of the model, the paper presents two image transforms: one performs an optimal enhancement of the dynamic range, and the other does the same for the mean dynamic range. Experimental results are shown.