Abstract

This paper addresses the problem of separating the illumination from the reflectance in images and compensating for non-uniform lighting. Recorded images of mural paintings suffer from significant losses in visual quality, compared to the direct eye observation when there are spatial or spectral variations in illumination. The visibility of detail in shadows is poor for recorded images and therefore an automatic computation is needed to improve them for better optical investigation. Images of medieval mural paintings, taken under very poor illumination conditions, are processed by the biologically inspired Retinex algorithm and by the equalize algorithm and the results are compared.

Highlights

  • The present paper represents an interdisciplinary approach of artworks investigation for the purpose of restoration and conservation, with respect to mural painting.There has been an increasing interest in last decades in interdisciplinary approaches of all areas of artworks restoration and conservation

  • That is why we propose the use of RAW files and Retinex algorithms that match human visual system for restorationconservation of fresco, as a non-destructive technique of image acquisition and not the gamma curves used in Photoshop

  • The Retinex algorithm depends on several parameters: Provenzi et al [6] showed that the qualitative behavior of Retinex in relation to the variation of these parameters can be predicted by using the mathematical definition

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Summary

Faculty of Mathematics and Computer Science

Abstract – This paper addresses the problem of separating the illumination from the reflectance in images and compensating for non-uniform lighting. Recorded images of mural paintings suffer from significant losses in visual quality, compared to the direct eye observation when there are spatial or spectral variations in illumination. The visibility of detail in shadows is poor for recorded images and an automatic computation is needed to improve them for better optical investigation. Images of medieval mural paintings, taken under very poor illumination conditions, are processed by the biologically inspired Retinex algorithm and by the equalize algorithm and the results are compared

INTRODUCTION
WHY BIOLOGICAL INSPIRATION?
Human perception
Colour constancy
DIGITAL IMAGING
THE RETINEX MODEL
The Retinex algorithm
RESEARCH METHODOLOGY
Retinex Histogram
Findings
CONCLUSIONS
Full Text
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