Back to articles
Articles
Volume: 18 | Article ID: art00015
Image
Color Accuracy-Guided Data Reduction for Practical LED-based Multispectral Imaging
  DOI :  10.2352/issn.2168-3204.2021.1.0.15  Published OnlineJune 2021
Abstract

The color accuracy of an LED-based multispectral imaging strategy has been evaluated with respect to the number of spectral bands used to build a color profile and render the final image. Images were captured under select illumination conditions provided by 10-channel LED light sources. First, the imaging system was characterized in its full 10-band capacity, in which an image was captured under illumination by each of the 10 LEDs in turn, and the full set used to derive a system profile. Then, the system was characterized in increasingly reduced capacities, obtained by reducing the number of bands in two ways. In one approach, image bands were systematically removed from the full 10-band set. In the other, images were captured under illumination by groups of several of the LEDs at once. For both approaches, the system was characterized using different combinations of image bands until the optimal set, giving the highest color accuracy, was determined when a total of only 9, 8, 7, or 6 bands was used to derive the profile. The results indicate that color accuracy is nearly equivalent when rendering images based on the optimal combination of anywhere from 6 to 10 spectral bands, and is maintained at a higher level than that of conventional RGB imaging. This information is a first step toward informing the development of practical LED-based multispectral imaging strategies that make spectral image capture simpler and more efficient for heritage digitization workflows.

Subject Areas :
Views 62
Downloads 19
 articleview.views 62
 articleview.downloads 19
  Cite this article 

Olivia Kuzio, Susan Farnand, "Color Accuracy-Guided Data Reduction for Practical LED-based Multispectral Imagingin Proc. IS&T Archiving 2021,  2021,  pp 65 - 70,  https://doi.org/10.2352/issn.2168-3204.2021.1.0.15

 Copy citation
  Copyright statement 
Copyright © Society for Imaging Science and Technology 2021
72010361
Archiving Conference
archiving
2161-8798
Society for Imaging Science and Technology
7003 Kilworth Lane, Springfield, VA 22151 USA