Exploring the Computational Future in Conservation and Heritage Preservation:

Mel Wachowiak and Keats Webb MCN 2011

wachowiakm@si.edu

3D Scanning

Microscopy &3D microscopy

Hyper- & Multispectral

Imaging---and more!

High Dynamic Range Imaging

Reflectance TransformationImaging

GigapixelImaging

Computational imaging the convergence of photography, computer vision, image processing, and computer graphics. Digital processing overcomes limitations of photography and it offers unprecedented opportunities for the enhancement and enrichment of visual media.

In the early days of the Smithsonian, photography had just been invented…and then later we used “film.”

Computational imaging part of integrated group of researchers at the Museum Conservation Institute, located just outside Washington.

• Structured Light

• Laser

• Photogrammetry

Group of Deer, 1941 Paul Manship 1885 -1966

32 1/2 x 27 1/2 x 19 in. (82.6 x 69.8 x 48.2 cm)

Gift of the artist 1963.14.2

Group of Deer Smithsonian American Art Museum

Final merged data, shaded point cloud

MCI contract engineer Anja Schmidt

Excellent hardware, software, and “wetware”

Model made from scan data (rear);

bronze cast awaiting patination

(foreground).

Early daguerreotype 80x70mm

1.8 Gigabyte image from microscopy mosaic.

112 images

All images shown from website screen shots

remember the flaw in the metal plate

It would only require 3000 images to reach resolution of the image at right (0.424mm wide). That’s 30x more than the giga-image.

Research microscope can achieve 5x this magnification, so about 15,000 images needed to reach 1 micrometer or less.

Fit for purpose!

5 stop difference, final 32-bit image; reduced to 8-bit for utility

Paper

Metals

Teeth & Bone

Paintings

Leather

Photo-graphic materials

Stone

RTI project examples

Extended Depth of Field

Z-Axis Scanning

Metrology-based

31 images in this stack

4mm trade bead from African bag

Before and after cleaning

Before and after cleaning

• While we can, when should we?

• n-dimensional: time and space, etc.

• Fit for purpose requires understanding of methods and resources.

• Who will use this data in 165 years?

If you can imagine it, it can be done.