A Detail description about LZW compression.

1. LZW
Compression

2. Compression:
 It is a process of reducing size by encoding it’s information
more efficiently.
 Due to this there is a reduction in the number of bits and bytes
used to store the information.
 A smaller file size is generated in order to achieve a faster
transmission of electronic files and a smaller space required
for its downloading.

3. LZW compression:
 LZW is the first letter of the names of the scientists Abraham
Lempel, Jakob Ziv, and Terry Welch, who developed this
algorithm.
 Is a lossless compression algorithm.
 It is simple and is dictionary based.

4. Working of LZW compression:
 It is a simple process.
 It replaces strings of characters with single codes.
 A new string of characters is added every time it sees to a
table of strings.
 Compression occurs when a single code is output instead of a
string of characters.
 The first 256 codes are by default assigned to the standard
character set.

5. Continue…
 Starts with a dictionary of all the single characters and
gradually builds the dictionary as the information is sent
through.
 Lossless compression hence works good for text compression.
 Uses a code table with 4096 as a common choice for number
entries.

6. Why to use LZW compression:
 Two reasons . . .
 For most palette color images LZW yields the highest
compression efficiency without sacrificing image data.
 The GIF image file format is the de facto standard for images
on the web. Most GIF files use the LZW compression.

7. LZW Algorithm:
 The LZW Compression Algorithm can summarised as follows:
w = NIL;
while ( read a character k )
{
if wk exists in the dictionary
w = wk;
else
add wk to the dictionary;
output the code for w;
w = k;
}

8. LZW Encoding:
 If the message to be encoded consists of only one character,
LZW outputs the code for this character; otherwise it inserts
two-or multi-character, overlapping.
 The last character of a pattern is the first character of the next
pattern.

9. LZW Encoding algorithm:
 Prefix←first input character;
CodeWord←256;
while(not end of character stream)
{ Char← next input character;
if(Prefix+ Char exists in the Dictionary)
Prefix ←Prefix + Char;
Else
{
Output : the code for Prefix;
insertInDictionary( (CodeWord, Prefix + Char) ) ;
CodeWord++;
Prefix←Char;
}
}

11. Example:

12. LZW Decoding:
 The LZW decompressor creates the same string table during
decompression.
 Initialize Dictionary with 256 ASCII codes and corresponding
single character strings as their translations.

13. LZW Decoding algorithm:
 output: string(firstCodeWord);
while(there are more CodeWords)
{
If(Current code word is in the dictionary)
Output: String(Current Code Word);
Else
Ouput: PreviousOutput+Previous Output First character;
Insert in the dictionary: Previous output+ current output First
character.
}

15. Example:

16. Advantages :
 This is a lossless compression technique, none of the contents
in the file are lost during or after compression.
 LZW algorithm is efficient because it does not need to pass the
string table to the decompression code.
 The table can be recreated as it was during compression, using
the input stream as data. This avoids insertion of large string
translation table with the compression data.

17. Disadvantages:
 What happens when the dictionary becomes too large?
 One approach is to throw the dictionary away when it reaches
a certain size.
 Useful only for large amount of text data when redundancy is
high.

18. Applications:
 A large English text file can typically be compressed via LZW
to about half its original size.
 LZW became very widely used when it became part of
the GIF image format in 1987. It may also (optionally) be used
in TIFF and PDF files.