Addressing Image Compression Techniques on current Internet Technologies

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Addressing Image Compression Techniques on
current Internet Technologies

• By Eduardo J. Moreira Onyeka Ezenwoye

CIS-6931 Term Paper
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Introduction

• Data compression focuses on the assumption that
  when transmitting data whether it be images,
  music, video and so on, one can benefit in the
  size and transmission times associated with such
  endeavors.

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Topics of Discussion

• Compression Types
• Run Length Encoding
• Huffman Coding
• PNG 0 (Portable Network Graphics)
• JPEG Graphics Format
• GIF Graphics Format
• MPEG Moving Picture Expert Group
• Conclusion

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Compression Types

• Lossless Recover of the exact original data
  after compression will be.
• Lossy Certain loss of accuracy in exchange for
  a substantial increase in compression.

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Run Length Encoding

• Lossles
• A simple technique achieves up to an 81
  compression ratio.
• Replacing multiple occurrences of a symbol with
  one copy and a count of how many times that
  symbol appears.
• ex. AAABBBCCCCCCCCCDDDDD encoded as 3A3B9C5D

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Run Length Encoding

• Can also be used to compress digital images by
  comparing pixels that appear adjacent to each
  other and only store the changes.
• Pros effective for encoding images with large
  white spaces or large homogeneous areas.

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Run Length Encoding

• Cons Does not work well when encoding files
  that contain even a small degree of variations
  among pixels. Because it uses 2 bytes to
  represent each symbol, these cases can actually
  cause an increase in file size.

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Huffman Coding

• Based on creating a variable length character
  code from frequent occurring characters.
• Avg. compression 25, Maximum 50 - 60
• Code words are composed of variable length binary
  strings.
• Binary string mapped to a different character
  within the file.
• Frequency distribution of characters created.
• Decide which code words will be used for each
  symbol.

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Huffman Coding

• Example
• USING HUFFMAN CODES
• Character Codeword Space required to represent
  all file characters
• (String length) (frequency of characters in
  file)
• _________________________________________________
  _______________________
• c 0 1(100,000)
• d 101 3(30,000)
• y 100 3(5,000)
• t 111 3(1,000)
• r 1101 4(50)
• z 1100 4(25)
• _________________________________________________
  _______________________
• Total Bits Required
  208,300
• _________________________________________________
  _______________________

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Dictionary Based Compression

• Encode variable length strings of symbols as
  single tokens.
• Tokens forms an index to a phrase dictionary.
• If tokens are smaller than the phrases, they
  replace the phrases and compression occurs.
• LZ77 is a sliding window technique in which the
  dictionary consists of a set of fixed length
  phrases found in a window into the previously
  seen text.
• LZ78 builds phrases up one symbol at a time,
  adding a new symbol to an existing phrase when a
  match occurs.

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JPEG Graphics Format

• Lossy
• Developed to compress gray-scale or color images.
• Stores 24bit color per pixel.
• JPEG can
• Achieve 101 up to 201 compression without
  visible loss.
• Achieve 301 up to 501 compression with small to
  moderate loss of quality
• Achieve up to 1001 for usage such as previews
  where low quality is not an issue.

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JPEG Graphics Format

• Drawback in time needed to decode and view the
  image.
• Well suited for real world photographs, scenic
  depictions of nature.
• Not been shown to work well with line drawings,
  cartoon animations, and other similar drawings.
• Viewed by the human eye not analyzed by machines.

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JPEG Graphics Format

• Flexibility, one has to create smaller lower
  quality images or larger higher quality ones by
  changing compression parameters.
• Extremely useful to a broad scope of real world
  applications.
• Example - What is the lowest amount of quality
  we need?
• We can control the actual decoding speed as it
  relates to the image quality by using inaccurate
  approximations instead of exact calculations.

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GIF (Graphical Interchange Format)

• Lossless
• Developed by Compuserve in 1987
• Two version GIF87a and GIF89a.
• Images have a bit depth of 8 bits per pixels,
  giving us a maximum of 256 colors.
• Image data is compressed using LZW (Lempel-Ziv)
  algorithm.

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GIF contd.

• Animation is accomplished by having many gif
  images together in one file.
• Best performance can be reached by using images
  with large percentage of solid colors throughout
  a wide portion of the image area.

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GIF contd.

• GIF89a extends the GIF87a specification and
  adds transparency, text comments, and animation
  of text.
• Becoming less used.

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PNG 0 Portable Network Graphic

• Lossless
• Uses modified Lempel-Ziv 77 algorithm, similarly
  being used by winzip, and other zip applications.
• Benefits of 15-35 percent higher compression.
• Works well with true color, palette, and
  grayscale color areas.

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PNG 0 Portable Network Graphic

• When compared to JPEG, this format offers higher
  image quality but the compression ratios are not
  as great as with JPEG.
• PNG 0 also uses filtering techniques. It is
  applied toward bytes of data before compression.
  This intern prepares data for optimal
  compression. This works best when applied to true
  color images.

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MPEG (Moving Picture Expert Group)

• Lossy
• Most popular video formats currently being used
  today.
• Major standards MPEG-1 and MPEG-2
• Remove spatial redundancy within a video frame
  and temporal redundancy between video frames
• DCT-based compression is used to reduce spatial
  redundancy

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MPEG contd.

• Motion-compensation is used to exploit temporal
  redundancy
• The idea of motion-compensation is to encode a
  video frame based on other video frames
  temporally close to it.
• Complicated and CPU intensive.
• Uses several algorithms to achieve as much as
  301 compression rate

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MPEG contd.

• Quantized Discrete Cosine Transform (QDCT).
• run-length encoding
• Huffman encoding

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Conclusion

• With the growing need to transmit more data in a
  faster manner, data compression is vital.
• Application determines what method is used.