Compression of the image

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Compression of the image

• Adolf Knoll
• National Library of the Czech Republic

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General schemes for application of compression

• The schemes adapt to the character of the
  represented objects
• Bitonal image (1-bit, black-and-white)
• Colour photorealistic image
• Mixed document (two above-mentioned components)

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Trends

• Bitonal
• from CCITT Gr. Fax 3 and 4 to JBIG variants
• Photorealistic
• Lossless compression PNG, TIFF/LZW
• Lossy from JPEG DCT to wavelet
• Mixed document
• Both applied (Mixed Raster Content usually
  vertically)

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How is it built into formats?

• Trying to have it in ISO TIFF (even JPEG, LZW, or
  PNG) but it is not enough due to lack of tools
  for conversion and display.
• That is why the other more suitable formats are
  used JPEG, PNG
• That is why there is a lot of development in the
  area of mixed formats they do not aim to become
  ISO

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Relevant directions

• Bitonal image
• JBIG2 (ISO) no support (exc. Xerox), but many
  similar activities
• Photorealistic image
• wavelet JPEG2000 and many other non-ISO
  initiatives (WI, LWF, IW44, SID, Imagepower IW,
  )
• Mixed content
• DjVu, LDF, Imagepower MRC

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Aims

• Image Archiving
• standardized archival format (TIFF, JPEG, PNG, )

• Image Delivery
• More efficient modern format (JB2, MrSID, DjVu,
  LDF, )

Which relationship will be between both of
them? It will be defined by the goal of the
project.
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Around compression

• Pre-processing of the image
• Compression
• Encoding in a format
• De-coding from the format
• De-compression
• Display print-out

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Pre-processing of the bitonal image - I

• Efficient schemes are built on possibilities to
  apply vocabularies of pixel chunks/groups
• E.g. a text is an image that can be interpreted
  as several dozens of images of letters, while the
  repeated occurrence of each letter can be
  represented by its coordinates (x,y) and
  reference to a dictionary in which there is only
  one representation of similar letters (digitized
  only once as a bitmap)
• This method is called PATTERN MATCHING, but

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Pre-processing of the bitonal image - II

• However, scanned texts have a lot of information
  noise in individual pixel chunks representing,
  for instance, letters in text
• Therefore, it is convenient to reduce differences
  between identically indentifiable chunks
• smoothing
• pixel flipping
• noise removal

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Smoothing and pixel flipping
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Problems in pattern matching
Ceská republika
Low quality original and/or scan inappropriate
processing
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Soft pattern matching

• Better work with dictionaries replacement only
  there, where the threshold value of the pixel
  chunk is satisfied
• If not, the whole small bitmap is stored
• Tuning of these mechanisms is a key to successful
  application of the lossy compression of a bitonal
  image.

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How to know

• Libraries have documents of various qualities-
  also very bad
• These documents are more difficult to process
  than good samples presented by software producers
• Tests tests tests on typical materials

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Bitonal compression

• Lossless (LZW, PNG, , CCITT Fax Group 3 a 4,
  JB2, JBIG, JBIG2, Algo Vision/Luratech (1-bit LDF
  component)
• Lossy modern schemes
• ATT (Lizardtech) (JB2) soft pattern matching
• ImagePower Inc. JBIG2 (JB2) only pattern
  matching
• Summus Inc. (Lightning Strike), ...

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GIF would be slightly worse than PNG
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Kvety ceské 19th century Czech journal
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Impact of the quality of digitized originals on
performance of compression schemes
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JB2

• Most efficient compression schemes JB2 from the
  DjVu format (ATT).
• It enables compression
• lossless
• lossy
• aggressive while preserving high quality

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JB2 as a component part of the DjVu format

• More files can be merged and saved into one (as
  PDF) they have the common dictionary so that
  together their size will be smaller than the sum
  of all individual files
• More files can be virtually joined (they are
  called one after another from the server)
• More advantages display, references, OCR,
  (DjVu plug-in)
• Expensive or free software for Linux or Solaris

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Samples and résumé

• Monitor and test new approaches for image
  processing
• They can be very suitable for document delivery
  services
• Image servers
• Scanned content
• CLICK!!!

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Which formats to use for bitonal image?

• If you have no special tools
• GIF
• If you wish smaller files, use PNG
• Both are recommended for WWW
• However, TIFF/CCITT Fax Gr. 4 is better
• Use DjVu, if you wish very small files

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Problems

• Good image editing software does not support TIFF
  with Gr. 4 encoding
• Display possible within normal Windows tools
• GIF and PNG support also higher brightness
  resolution (8-bit / 24-bit) take care not to
  save bi-level image in higher image depth
• DjVu necessary to solve authoring software
  problem

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Lossy compression bitonal image
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Compression of colour images

• Lossless
• LZW
• GIF (8-bit only)
• TIFF (5.0)
• PNG
• Wavelet
• JPEG2000 (JP2)

• Lossy
• DCT (JPEG)
• Fractals
• Wavelet
• IW44
• LWF, WI
• JPEG2000 (JP2)
• MrSID,

Classical (LZW, RLE, DCT) versus wavelet
approaches.
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True colour image
DCT
wavelet
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Testing compression efficiency

• Sample
• Reference
• Full-colour (JPEG, wavelet)
• 1-bit (establish tresholds Paint Shop Pro,
  LuraWave)
• MRC (same sample DjVu Solo)

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Compression efficiency bitonal image
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Compression efficiency
True colour
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How to apply compression?

• It depends on the character of objects in the
  image
• Photorealistic image (JPEG, wavelet)
• Text and simple blac-and-white graphics (Fax
  Group 4, JB2, )
• Colour graphics (problem to compress with losses
  better lossless PNG or GIF application area
  of vector graphics - SVG)
• Mixed content (composed solutions DjVu, LDF, )

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The most efficient solution

• To segment images into two or more groups of
  objects
• Objects good for bitonal conversion
• Objects good for true colour representation
• Tto compress each group separately and then merge
  into one format.

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Horizontal segmentation/zoning

• Horizontally
• Text
• Grafics
• Photographs
• Imagepower Inc.

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Vertical segmentation/zoning

• Vertically
• Foreground
• Background
• Lizardtech Inc. (ATT)
• Luratech GmBH
• DjVu, LDF

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Comparison of DjVu and LDF

• DjVu
• 6 layers
• Foreground
• JB2
• IW44
• Background
• 4 layers IW44

• LDF
• 3 layers
• Foreground
• LDF 1-bit Comp.
• LFW
• Background
• 1 layer LWF, JP2

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Bitonal versus composed image
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Grey level
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Other DjVu properties

• More images in one
• as TIFF, PDF, LDF, , with use of the common
  dictionary of pixel chunks
• Virtually pages remaion on server and only that
  page that is called is delivered

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Multiresolution image

• MrSID
• In one file several (up to 8) images in various
  resolutions
• Sample
• Efficient with an image server

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SAMPLES

• Samples of various compression solutions