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 Cost Original may only withstand one scan Maintenance of digital files 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 image quality and utility CUL s Approach to Imaging No More No Less desired point of capture Image requirements and cost 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 zoom in Effects of Resolution 600 dpi 300 dpi 200 dpi 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 threshold 60 threshold 100 11 Bit Depth Determined by the number of binary digits bits used to represent each pixel 1 bit 8 bit 24 bit Bit Depth increasing bit depth increases the level of gray or color information that can be represented and arithmetically increases file size Bit depth dynamic range and color appearance Utilizing Sufficient BitDepth 3 bit gray 8 bit gray Utilizing Sufficient Bit Depth 8 bit color 24 bit color Bit Depth vs Dynamic Range The range of tonal difference between lightest light and the darkest dark Mapping Tones Correctly Use of Histograms Representing Color Appearance Balanced Color Color Shift Towards Red Image Enhancement Image editing to modify or improve an image filters brightness contrast sharpness blur tone and color correction Use raises concerns about fidelity and authenticity Effects of Filters no filters used maximum enhancement Image Editing Compression reduces file size for processing storage transmission and display image quality may be affected by the compression techniques used and the level of compression applied Compression Variables lossless versus lossy compression proprietary vs open schemes level of industry support bitonal vs gray color see attributes of common compression techniques at www library cornell edu preservation tutorial pr esentation table7 3 html Effects of JPEG Compression 300 dpi 8 bit grayscale uncompressed TIFF JPEG 18 5 1 compression Compression File Format Comparison GIF lossless File Size 60 KB JPEG lossy File Size 49 KB images courtesy of Edison Papers File Formats Consist of both the bits that comprise image information and header information on how to read and interpret the file Image quality affected by format support for Bit depth Compression techniques Color management Hardware software and network support See common file formats chart at www library cornell edu preservation tutorial presentati on table7 1 html Equipment used and its performance over time scanners with same stated functionality can produce different results Factors affecting image quality Optical mechanical and sensing components Calibration Age of equipment Environment Variations in Image Quality due to Scanner Performance 300 dpi scanner A 300 dpi scanner B Correlating Document Attributes to Image Requirements Example Determining Resolution Requirements What s you finest feature What s your quality requirement What s your imaging approach Case Study Brittle Books Variables feature size quality imaging approach Bitonal QI formula for text fixed metric smallest lower case letter QI values 8 excellent 5 good 3 6 marginal Resolution key to text capture e g dpi DPI 3QI 039h 600 dpi 1 bit capture adequately preserves informational content of cleanly produced text and supports image processing e g OCR Textual Documents May Require Tonal Capture Pages badly stained Pages exhibit low contrast between text and background Fine features not fully resolved Pages contain complex graphics color or important contextual information Gray color QI formula for text Dpi 2QI 039h Determining Resolution Requirements beyond Text Stroke width Finest scale Visual perception Defining Detail as Stroke Edge based representations Variables feature size quality imaging approach fixed metric width of finest line stroke dot or marking QI values based on sampling frequency 2 excellent 1 5 good 1 marginal Resolution and bit depth key to quality Defining Detail as Stroke QI formulas for stroke Gray color dpi QI 039w QI dpi x 039w Bitonal dpi 1 5QI 039w Adequately Rendered Stroke Inadequately Rendered Stroke Example Manuscript page with finest significant stroke measuring 2mm which must be fully captured Gray color dpi QI 039w QI 2 w 2 Dpi 2 039 2 256 dpi Defining Detail as Scale Smallest significant scale or repeatable pattern e g knots in a rug vs strands in the thread Can result in very high resolution requirements e g photographs book illustrations Halftones scan at 4 times the screen ruling utilize special descreen rescreening or scan in grayscale 400 dpi is a good default Halftone Scanned at 150 DPI Halftone Scanned at 400 DPI Defining Detail Based on Visual Perception Human eye can detect details approximately 1 215 inch wide Finer details are optically averaged Using two pixel rule visual perception requirements met at 430 dpi Illustrated Book Study 400 dpi grayscale recommendation www library cornell edu preservation illbk AdComm ht m Detail Represented at 400 dpi Translating Between Digital Resolution and Scanner Performance Detail capture