From Analog to Digital

Peter HirtleHBCU-CUL Digital Imaging

Workshop IIJuly 31, 2007

Session Goal

Workshop participants will understand the issues involved in converting analog materials into digital formats for preservation

and access.

Session Objectives Overview the application of the

scanning process in the digitization chain

In-depth presentation on the factors affecting image quality

Discuss the issues involved in presentation

Participate in “reality checks” on lessons learned

Learner Outcomes Be able to Discuss issues involved

in converting analog materials to digital images

Compare and Contrast three types of image scanning

Understand factors affecting image presentation

Analog to Digital

We’re scanning 2D images – (textual and graphical) & 3D images (photographic)

Other 3D images are tape-based, such as: Video Audio

What are Digital Images? “electronic photographs” created through

scanning or digital photography Sampled 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

Digital Image Also known as a raster or bitmap

image

Three types of scanning BITONAL GRAYSCALE

COLOR

Bitonal Scanning

Information is presented as either black or white

Gray shades simulated by clustering black dots

Suitable for printed materials

Grayscale Scanning Shades of gray

represented; normally 8 bits per pixel Suitable for

manuscripts, photographs, halftones, and stained documents

Bitonal vs. Grayscale Capture of Stained Manuscript

Bitonal scan Grayscale scan

Color Scanning Full color range; normally

24 bits per pixel Suitable for documents

with significant color information, such as photographs, works of art

Helpful in determining a document’s age, physical condition, or previous use

Digital Image Quality Affected By

Document attributes Resolution and threshold Bit depth and dynamic range Image enhancement Compression/format Equipment and performance over

time Operator judgment and care

Important Document Attributes Physical type, size, and

presentation Physical condition Document type The Big Three

Detail, Tone, Color

Scanned from OriginalOn H-P ScanJet 3c

Scanned from 2N FilmOn Sunrise SRI 50

Halftone: 1-bit image at 400 dpi

600 dpi 1-bit2.9 Mb file

400dpi 8-bit10.3 Mb file

400 dpi 24-bit30.9 Mb file

Matching Informational Content to Scanning Approach: Quality vs. File Size and Cost

Resolution Determined by number of pixels used to

represent the image expressed in dots per square inch (dpi)

zoom in

Resolution

100 dpi = 1002 (100 x 100) or 10,000 dots

200 dpi = 2002 or 40,000 dots

400 dpi = 4002 or 160,000 dotsincreasing resolution increases detail

captured and geometrically increases the file size

Effects of Resolution

600 dpi600 dpi

300 dpi300 dpi

200 dpi200 dpi

Threshold Setting in Bitonal Scanning

defines the point on a scale from 0 (black) to 255 (white) at which gray values will be interpreted either as black or white

0 255black dark

gray lightgray

white

Effects of Threshold

threshold = 100

threshold = 60

Defining Detail in Text Fixed metric: smallest lower case letter Variables: quality, resolution, feature

size Bitonal QI formula for text

dpi = 3QI/.039h QI values: 8(excellent), 5(good),

3.6(marginal), 3(barely legible) Grayscale/Color QI formula for text

dpi = 2QI/.039h

Example Text page with smallest character

measuring 1mm, which must be fully captured (QI=8, h= 1)

Bitonal Scanning: dpi = 3QI/.039h dpi = 3(8)/[.039(1)] = 615 dpi

Grayscale: dpi = 2QI/.039h dpi = 2(8)/[.039(1)] = 410 dpi

http://images.library.uiuc.edu/projects/calculator/

Bit Depth Determined by the number of

binary digits (bits) used to represent each pixel

1-bit 8-bit 24-bit

Bitonal scanning has a bit-depth of 1

each pixel represented by one bit, with a tonal range of 2:

0 = black 1 = white

Binary Calculations

21 = 222 = 423 = 824 = 1628 = 256210 = 1024212 = 4096224 = 16.7 million

Bit Depth

Grayscale is typically 8 bits or more, representing 256 (28) levels

Color is 24 bits or more , representing 16.7 million (224) levels

example: 8-bit grayscale pixel 00000000 = black 11111111 = white

Bit Depth

increasing bit depth increases the levels of gray or color that can be represented and arithmetically increases file size

affects resolution requirements

Effects of Grayscale on Image Quality

3-bit gray 8-bit gray

Tonal Reproduction Dynamic range: the range of tonal

difference between lightest light and darkest dark

The higher the range, the greater the number of potential shades

Tone distribution as important as dynamic range

Comparing Key Types

Mapping Tones Correctly: Use of Histograms

Color Appearance Difficult to evaluate Hue, saturation, brightness Translating between analog and

digital, between color spaces, between reflected and transmitted light

Representing Color Appearance

Balanced Color

Color Shift Towards Red

Color Cast

Color Imaging and Tone Distribution

Limited tones evident in highlights and shadows

Balanced tonal distribution

Image Processing and Enhancement

Image editing to modify or improve an image filters (brightness, contrast, sharpness,

blur) file size reduction (scaling) tone and color correction

Effects of FiltersEffects of Filters

no filters usedno filters used

maximum maximum enhancementenhancement

Compression/format

image quality may be affected by the compression technique used to reduce file size

Image quality affected by format support for: Bit depth Compression techniques Color management

Compression /File Format Comparison

GIF (lossless)File Size: 60 KB

JPEG (lossy)File Size: 49 KB

images courtesy of Edison Papers

Equipment used and its performance over time

scanners offer wide range of capabilities to capture detail, tone, dynamic range, and color

scanners with same stated functionality can produce different results

calibration, age of equipment, and environment are also factors

300 dpi, scanner A 300 dpi, scanner B

Variations in Image Quality due to Scanner Performance

Image Capture:

Creating digital files rich enough to be useful over time in the most cost- effective manner.

Why Create High Quality Images?

preservation original may only withstand one scan

cost one scan may be all that is affordable

access one scan can be used to derive

multiple images

Calculating File Size

F file size = height x width x bit depth x dpi2

8

File Size Naming Conventions

Represented in bytes

1 byte = 8 bits 1Kb ~ 1,000 bytes 1Mb ~ 1,000Kb 1Gb ~ 1,000Mb

Example: grayscale image

file file size = height x width x bit depth x dpi2

8

7”

10”

300 dpi, 8-bit

file size = 10 x 7 x 8 x 3002

8

file size = 6,300,000 bytes = 6.3 megabytes

800

200 dpi , 1 bit

10”

8”

Example: Bitonal Imagefile size = height x width x bit depth x dpi2

8

file size = 10 x 8 x 1x 2002

8

file size = 3,200,000 bytes = 3.2 megabytes

Reality Check 1

Determine the file size of a letter size page captured bitonally at 200 dpi.

Answer

(8.5 x 11 x 2002)/8 = 468Kb or .47Mb

Reality Check 2

Determine the file size of an 8” x 10” photograph scanned in color at 200 dpi.

Answer

(8 x 10 x 24 x 2002) = 9.6 million

bytes or 89.6Mb

Estimating File Size for Compressed Images Compressed file size = file size

level of compression

Example: Color photo compressed 20:1

9.6Mb =.48Mb 20

Aligning Document Attributes with Digital Requirements Identify key document attributes

Detail, tone, color Characterize them, if possible through

objective measurements Determine quality requirements and

tolerance levels Translate between analog and digital

and between scanning requirements and scanning performance

Aligning Document Attributes with Digital Requirements Calibrate scanner, calibrate the

rest of the system Control lighting and environment Objective and Subjective

Evaluation: targets and software; evaluating images against the originals

Aligning Document Attributes with Digital Requirements Minimize post-processing in the

master image Save in TIFF; use RGB for color;

and avoid lossy compression Maintain scanning metadata

One Size Does Not Fit All!

different document types will require different scanning processes

the more complex the document, the higher the conversion/access requirements, the larger the file, and the greater the expense

scan the original whenever possible Follow project recommendations