Multispectral camera and radiative transfer equation used to depict Leonardo's sfumato in Mona Lisa

Abstract

The technique used by Leonardo da Vinci to paint flesh tints--the sfumato--has never been scientifically depicted until now. From 100,000,000 reflectance spectra recorded on Mona Lisa, a virtual removal of the varnish is first obtained. A unique umber pigment is then identified in the upper layer and an exceptional maximum of the color saturation is underlined, both characteristics of a glaze technique. The modeling calling upon the radiative transfer equation confirms this maximum of saturation, the identification of an umber in the upper layer, and moreover underlines a mixture of 1% vermilion and 99% lead white in the base layer. Finally, the modeling, using the auxiliary function method, explains the spectacular maximum of saturation by the multiple scattering.

Revealing the sfumato Technique of Leonardo da Vinci by X‐Ray Fluorescence Spectroscopy

“…This technique is based on the superimposition of translucent paint layers rich in organic medium with low pigment content. Optical methods confirmed the presence of glazes on the Mona Lisa painting,4, 14 but they gave no information about their composition and thickness.…”

The Mona Lisa Decrypted: Allure of an Imperfect Reality

“…The smile may be due to da Vinci's experiments with a technique called sfumato, which allows tones and colors to fade into each other without discrete lines like smoke or blurred dimensions. 15 Certainly, we should also admit that our unifying theory may be as plausible as the multiple explanations provided, each open to individual and collective bias. In summary, we believe that the enigma of the Mona Lisa can be resolved by a simple medical diagnosis of a hypothyroidismrelated illness that could have been the result of a peripartum thyroiditis accentuated by the living conditions of the Renaissance.…”

Illumination-robust multispectral demosaicing

“…Multispectral images are acquired in different illumination conditions for various application fields such as medical imaging [1], precision agriculture [2], art studies [3], vision inspection for food quality control [4] or waste sorting [5]. The information available in each channel of a multispectral image results from a spectral integration of the product between the scene reflectance, illumination, camera filter transmittances and sensor sensitivity.…”