1. Introduction to Digital Imaging
Digitisation Of Heritage Materials
Introduction to Digital Imaging
CCHAD Project
Introduction to Digital Imaging

2. Digital Capture Analogue to Digital Conversion Storage Analogue signal
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Digital Capture
Analogue to Digital
Conversion
Storage
Analogue signal
Digital Signal
CCD or CMOS
RGB Filters
Lens
Original
Introduction to Digital Imaging

3. Pixels arranged in a grid
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Bitmap (raster) image concept
Pixels arranged in a grid
Introduction to Digital Imaging

4. Bitmap (raster) image - pixels
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Bitmap (raster) image - pixels
Pixel colour information may be stored and
expressed in many different ways
PIXEL VALUES R: 227 G: 192 B: 162
PIXEL VALUES R: 0 G: 0 B: 0
RGB = 227, 192, 162
RGB = 0, 0, 0
One of the most common
approaches is to use
RGB values
RGB = Red, Green, Blue
Introduction to Digital Imaging

5. 2 shades - black and white
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B & W images– bit depth
256 shades of grey
(8-bit)
16 shades of grey
(4-bit)
4 shades of grey
(2-bit)
2 shades - black and white
(1-bit)
Sometime used for text digitisation
(saves storage space and computing power)
Introduction to Digital Imaging

6. Colour images Indexed colour 16 colours Indexed colour 64 colours
RGB 24-bit image
16.7 million colours
Indexed colour
256 colours

7. Quality Digital Images Suitable for archiving
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Quality Digital Images Suitable for archiving
Technically
Minimum - 24 bit (RGB) colour OR
Minimum – 8-bit greyscale
Visually
Over 16.7 million colours possible in the image (24-bit RGB)
256 shades of grey (greyscale)
Introduction to Digital Imaging

8. Resolution of an Image Higher resolution Low resolution
(larger number of pixels)
Low resolution
(small number of pixels)

9. Distance and resolution
Camera is close to the object
(more pixels assigned to the image)
CCD
Camera is far from the object
(less pixels assigned to the image)
CCD

10. Resolution Limits High resolution system Pixels clearly defined
Low resolution system
Pixels defined poorly

11. RGB - Red, Green, Blue Primary Colours in Digital Images
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RGB - Red, Green, Blue Primary Colours in Digital Images
Additive colour model
Based on how a human
eye perceives colour and deals with light being emitted by a light source. Primary
colours (red, green, blue) are added together in varying intensities to produce broad array of colours.
Employed in:
Computer monitors
Television screens
Digital scanners
Digital cameras
Introduction to Digital Imaging

12. Computer Screens Magnified
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Computer Screens Magnified
CRT screen
(old technology)
LCD screen
1 pixel
Colour as perceived by the eye
Introduction to Digital Imaging

13. CMYK Cyan, Magenta, Yellow, blacK
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CMYK Cyan, Magenta, Yellow, blacK
Subtractive colour model
Used when mixing paints,
dyes, inks and colorants.
Each colour is produced
by the mixture absorbing
some wavelengths of light
and reflecting others.
Employed in:
Most printing processes
Theoretically it should only be cyan, magenta and yellow colours employed in the model. Real life pigments or inks, however, are not pure enough to create good blacks. This is why the fourth colour – black (K) has been added to the process.
Introduction to Digital Imaging

14. CMYK print Most popular printing processes use CMYK techniques
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CMYK print
Most popular printing processes
use CMYK techniques
Introduction to Digital Imaging

15. (shades of colour or grey)
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Capturing tones
(shades of colour or grey)
Gradual change from darker to lighter shade
Human eye and conventional film:
Black
White
Clearly defined steps between different shades (sampling)
Digital image:
255
Introduction to Digital Imaging

16. What’s Inside Camera/Scanner?
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What’s Inside Camera/Scanner?
Electronic Imagers
CCD – Charge-Coupled Device
CMOS – Complementary Metal-Oxide Semiconductor
Virtually all current digital capture devices use these technologies.
Both CCD and CMOS are solid state devices converting light photons into electric current. They are mono-chromatic and can capture black and white images only.
Introduction to Digital Imaging

17. CCD & CMOS capture of colour
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CCD & CMOS capture of colour
RGB filters on top of CCD (Bayer pattern)
CCD or CMOS R G B
RGB filters in the camera split the incoming (through the lens) image into three primary channels – red, green and blue. In fact, the camera captures three separate images that are combined (by the camera or computer’s software) into full colour image.
Introduction to Digital Imaging

18. Image Exposure Digital Camera
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Image Exposure Digital Camera
Image correctly exposed
(correct amount of light entering camera)
Image over-exposed
(too much light entering camera)
Image exposure is regulated by either
time that the CCD is “available” for recording the image – controlled by the SHUTTER SPEED OR
amount of light allowed to enter the camera – controlled by the APERTURE ( a bit like a pupil in the eye)
Image under-exposed
(not enough light entering camera)
Introduction to Digital Imaging

19. Brightness Perception
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Brightness Perception
Print
Range
Monitor
Range
Digital Camera
Range
Human Eye
Range
Introduction to Digital Imaging

20. Dynamic Range Low quality camera. Small dynamic range
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Dynamic Range
Low quality camera.
Small dynamic range
No detail in shadows
Introduction to Digital Imaging

21. Dynamic Range Higher quality camera. Larger dynamic range
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Dynamic Range
Higher quality camera.
Larger dynamic range
Much better detail retained
Introduction to Digital Imaging

22. Resolution and printing dpi = dots per inch (linear)
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Resolution and printing dpi = dots per inch (linear)
On screen:
Printed:
1,200 pixels wide image
4 inches wide
at 300dpi:
2 inches wide
at 600dpi:
Introduction to Digital Imaging

23. Resolution Examples: Cam_pix Res = Mat_size
Calculating maximum size of the original material that your camera can capture
Find your camera’s frame capture size (in pixels). Use the longer edge value (Let’s call this value: Cam_pix).
Measure longer edge of the original material in inches (Let’s call this value: Mat_size).
Divide Cam_pix by Mat_size and write down the result (Res).
To achieve the archival quality capture Res should be equal to or larger than 300.
If digitising to higher standards or small original material, Res is usually equal to or larger than 600.
When capturing from film (negatives, slides), Res usually needs to be in excess of 2,000.
Examples:
Camera frame size (in pixels)
Approx. Megapixels
Approx. maximum longer edge of the material (at 300dpi - in inches)
Approx. maximum longer edge of the material (at 600 dpi - in inches)
2048 x 1536 3
6.5
3.5
2592 x 1944 5
8.5 4
3264 x 2448 8
10.5
3872 x 2592 10
12.5 6
4672 x 3104
14.6
15.5
Res =
Mat_size
Cam_pix
IMPORTANT:
The captured image has to fill the frame completely to achieve calculated resolution

24. Image Capture - Scanners
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Image Capture - Scanners
A/D Conversion
Computer
Introduction to Digital Imaging

25. Dynamic Range of scanners (Rough guide to scanner’s quality)
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Scanners - quality
Maximum optical resolution v. interpolated resolution
Dynamic range
Quality of the lens and other elements
Dynamic Range of scanners (Rough guide to scanner’s quality)
Up to 3.0: Poor
Up to 3.5: Better
3.5 to 3.7: Good
Above 3.7: Very good
Above 4.0: Excellent
Be aware that scanner manufacturers often exaggerate the dynamic range figures
Introduction to Digital Imaging

26. Successful Digitisation
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Successful Digitisation
Colour calibration of devices and computers
Adequate lighting and setup of the camera
Adequate capture resolution
Proper handling of materials
Introduction to Digital Imaging

27. Image manipulation Cropping, rotating Correcting colour
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Image manipulation
Image manipulation should be kept to minimum in Archival Digitisation workflow
Cropping, rotating
Correcting colour
(while using proper tools on colour calibrated systems)
Removing dust spots? (film scanning)
Converting to archival formats
Manipulation for delivery (web, print)
Introduction to Digital Imaging

28. How to store images - media
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How to store images - media
CD-R or DVD (optical discs) – not recommended (will become obsolete soon; cumbersome and time-consuming to migrate data from)
“Archival” Digital Tape (usually available to large organisations only – expensive)
Internal & External Hard Disk Drives Currently, the safest, practical way to store large collections of images. Data needs to be re-freshed (re-written) every 5 years.
Cloud storage Good, additional option. Can be expensive and slow. Does not guarantee absolute safety.
Introduction to Digital Imaging

29. How to store images - formats
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How to store images - formats
RAW
Generic name for all sorts of CCD-level (image processing kept to minimum) formats. Due to proprietary nature not suitable for archiving and should be converted to DNG.
DNG (Digital Negative)
Adobe’s new, open standard for RAW format images, probably suitable for archiving.
TIFF (Tagged Image File Format)
One of the most common and best formats to use in Digital Archiving
JPEG (Joint Photographic Experts Group)
Best format for the internet, not suitable for archival images (uses lossy compression)
JPEG 2000 (Joint Photographic Experts Group)
Can use lossless compression, great for delivering large images over the internet. Due to copyright issues with the JPEG 2000 standard and limited number of practical implementations its archival qualities are still unclear.
Introduction to Digital Imaging

30. Lossy Compression Example (Not recommended for archival masters)
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Lossy Compression Example (Not recommended for archival masters)
Low compression -
Smaller number of images stored on the disk but better image quality
Minimal loss
Visible loss
High compression -
Larger number of images stored on the disk but lower image quality
Introduction to Digital Imaging

31. How to store images - Fixity
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How to store images - Fixity
After image is in its final form, it’s a good idea to create a checksum for it.
How it is done:
Special software applies a mathematical algorithm to a digital file.
The result is a unique string of numbers and letters. It is absolutely unique for a given file and any changes to this file will result in a production of completely different checksum.
There are many types of checksums. Currently, digital preservation professionals recommend SHA256 (safer) or SHA1 (faster).
Checksums need to be stored with files, so they can be checked periodically.
SHA256 example string (64 characters): 3d753ae0edc96e4b377b94bd3eb3f7c001c21fe271ada643be3fbf55906e5792
SHA1 example for the same file (40 characters): eff2b1adceb7a1221a4e19756e0d1f70091a6423
Introduction to Digital Imaging

32. How to store images - DAMS
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How to store images - DAMS
DAM or DAMS – Digital Asset Management (System) software
Good DAMS features:
Enables safe and secure collection, management and delivery of digital assets
Enables multi-user workflows
Provides means of fast and accurate searching
Helps in digital preservation efforts
Some examples of DAMS:
Rosetta
Dspace
ResourceSpace
Recollect
Piction
many, many more…
Introduction to Digital Imaging

33. CCHAD Project, Coffs Harbour Council
Digitisation Of Heritage Materials
CCHAD Project, Coffs Harbour Council
Andrew Stawowczyk Long Phone:
Introduction to Digital Imaging