3.3.8 Data Compression

• Files, especially graphic and audio files, can become very large. Here are some intersting facts:
  • On Facebook more than 350 million images are uploaded each day. On Snapchat 8,796 images are uploaded per second. It has been estimated that over 3.2 billion images are uploaded to social media sites each day!
  • Every day millions of audio and video files are being downloaded.
• When data is transmitted across the Internet, it will go through many different physical links between routers.
• The connection from a computer or a LAN into the Internet is likely to be the slowest part of this route, as you probably know from experience.
• At home you may have quite a slow network connection and it may take a while for web pages to load.
• One way of speeding the rate at which files can be transmitted across the Internet is to compress them to make them smaller. Smaller files take less time to transmit over a network.
• Understanding how compression affects files is important, as the type of compression selected will affect how the image looks or the audio track sounds. The final use of the file will dictate how much you can compress the files and still have a file that is uasable.

• To summarise, compression is used in order to:
  1. Reduce the amount of storage needed on a computer to save files.
  2. Allow large files to be transmitted as an email attachment; many email servers limit the size of a file that can be sent and compression can reduce the file size to allow users to send it.
  3. Allow a file to be transmitted in less time, due to the smaller file size.
  4. It reduces congestion on the Internet through smaller files.
  5. It makes audio and video files suitable for streaming.

Lossy Compression

• Is a data encoding method where files are compressed by removing some of the detail. For example, photographs can be stored using fewer colours so fewer bits are needed per pixel.
• This type of compression is used to compress images, audio and video files.
• That is why it cannot be used for text files or program files - A book with many missing words would be unreadable!
• But lossy compression can be used for graphic and audio files as they contain much data that can be discarded.
• The most commonly used compression technique for graphic files was developed by the Joint Photographic Experts Group and produces JPEG files with the extension .jpg.
• Here are two photographs to show the differences:

Lossless Compression

• With a lossless data encoding method, a file is compressed but no data is lost and the file can be decompressed with all of its information intact.
• For example, bank records must keep all of the data; you cannot transmit a bank statment and miss out a few zeros because they don't matter too much!
• It could be used to compress data files, for example by Zipping them using a utility program such as WinZip, before attaching them to an email.

The size of an image file depends on the colour depth and dimensions. The size of an audio
file depends on the sample rate and bit depth. The size of an image file and an audio file
can be very large.

• Run Length Encoding (RLE) is a simple form of lossless data compression which works by reducing the physical size of a sequence of

data having the same value and are stored using requency/data pairs.

• This repeating string, called a run, is encoded into two bytes.
• The first byte represents the number of characters in the run and the second gives the character.
• For example, let's look at the following string:
  • aaabbbbbbccccccccc
  • This string length is 18 bytes.
  • Using run length encoding, this could be compressed to:
  • 3a6b9c
  • This string has been reduced to 6 bytes using RLE.

• RLE provides very good compression ratios where there are long runs of one particular value like the following 1-bit black and white image:

• When represented by a letter, the size of the file is 64 bytes: 8 bytes per line.
• Using Run Length Encoding will reduce the file size of this one character from 64 bytes to 48 bytes.

• Huffman coding, also known as Huffman Encoding or Huffman Compression. Is an algorithm for lossless compression based on the frequency of the characters or symbols in the file.
• It ensures that the more common characters have fewer bits to represent them than the less common characters that need more bits to identify them.
• Therefore the overall size of the file is reduced.
• It is therefore called a variable-length coding system because the codes for different characters have different lengths.
• Huffman coding uses a structure called a Binary Tree, which consists of a root node and a number of nodes and branches as shown in the diagram below: