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From Analog to Digital
What are Digital Images?
Electronic snapshots taken of a scene or scanned from documents
samples and mapped as a grid of dots or picture elements (pixels)
pixel assigned a tonal value (black, white, grays, colors), represented in binary code
code stored or reduced (compressed)
read and interpreted to create analog version
CUL Bias on Image Capture:
Create rich images that are useful over time in the most cost-effective manner.
Set conversion requirements greater than immediate application
Promote reuse of content
Enable sharing parable and trusted resources across disciplines, users, and institutions
Why Rich Digital Masters?
Preservation
Original may only withstand one scan
Maintenance of digital files
Cost
One scan may be all that is affordable
Conversion costs dwarfed by other costs
Access
Many from one
The richer the file, the better the derivative in terms of quality and processibility
How to determine what’s good enough?
Connoisseurship of document attributes
Identify key information content
Objectively characterize or measure attributes: size, detail, tone, and color
Appreciate imaging factors affecting quality and cost
Translate between analog and digital
Equate measurements to digital equivalencies and corresponding metrics, ., detail size  resolution  MTF
CUL’s Approach to Imaging: “No More, No Less”
Image requirements and cost
image quality and utility
desired point of capture
Digital Image Quality is Governed By:
resolution and threshold
bit depth
color management
image pression and file format
system performance
Resolution
Determined by number of pixels used to represent the image
Increasing resolution increases level of detail captured and geometrically increases file size
zoom in
Effects of Resolution
600 dpi
300 dpi
200 dpi
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Threshold Setting in Bitonal Scanning
defines the point on a scale from 0 to 255 at which gray values will be interpreted either as black or white