Spectral Optimization to Minimize Light Absorbed by Artwork

Abstract

Light is needed to appreciate artwork, but visible radiation causes damage by photochemical action. Photons trigger photochemical action only when they are absorbed by the object. Damage to sensitive materials can be reduced by optimizing the spectrum of a light source to the reflectance factor of a museum artifact. Absorption minimization approaches can be utilized to quantify and optimize typically conflicting parameters, such as damage due to light absorption, color quality of artwork, and energy consumption. In this project, seven narrowband light emitting diodes (LEDs) are optimized using a multi-objective genetic algorithm to reduce light absorption and energy consumption, while maintaining the color appearance of five paints (blue, green, yellow, orange, red). Results indicate that optimized test spectra can reduce light absorption between 18% and 48%, without causing perceptible color or hue shifts in the paintings. Parallel to absorption, energy consumption is almost halved for all of the paints (between 42% and 48%). Optimizing the light source spectrum can aid in conservation of art collections in museums by reducing damage caused by optical radiation while preserving color fidelity.

Appearance of Achromatic Colors Under Optimized Light Source Spectrum

“…Test samples with plateau type reflectance resulted in higher light absorption and energy consumption compared to other reflectance types. The plateau type test samples showed a similar trend in a previous study [19].…”

“…Although optimizing SPDs using the MOGA yielded results similar to previous studies [6], [7], [19] when compared to standard illuminants (equal-energy radiator and incandescent), energy consumption values were higher when optimized test SPDs were compared to the pcLED. This may be due to the spectral optimization method used by the MOGA, which assigns a weighting value (x i in eq.…”

“…Overall, SPDs optimized for plain type reflectance (achromatic samples) induced imperceptible color shifts and resulted in reduced light absorption and energy consumption. The multi-objective algorithm calculated energy savings similar to previous studies [6], [7], [19], except when the reference was a pcLED. The linear optimization method performed better than multi-objective genetic algorithm for achromatic samples when the object color appearance was matched relative to the pcLED.…”

“…Achromatic objects do not need to reflect power in all wavelengths, due to their relatively flat spectral response functions, so it can be hypothesized that the MOGA failed to find truly optimal solutions for achromatic colors. A two-peak linear optimization method that was used in previous studies [6], [7] was used to explore this idea by optimizing SPDs for achromatic samples (samples [19][20][21][22][23][24].…”

“…The optimization process ends when a feasible solution is found, a predetermined number of maximum generations is reached, or the fitness of the highest-ranking solution reaches a plateau. MOGAs have been previously used in lighting optimization for color rendition metrics [17], [18], reducing damage to artwork [19], energy efficiency [20], visual preference [21], and the uniformity and efficiency of roadway lighting [22]. Readers can refer elsewhere [23] for a detailed discussion of the light optimization studies.…”