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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 of comparable 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, e.g., detail size ? resolution ? MTF CUL’s Approach to Imaging: “No More, No Less” Digital Image Quality is Governed By: resolution and threshold bit depth color management image enhancement compression 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 Effects of Resolution 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 Effects of Threshold Bit Depth Determined by the number of binary digits (bits) used to represent each pixel Bit Depth increasing bit