Coded data generation or conversion – Digital code to digital code converters – Unnecessary data suppression
Reexamination Certificate
2001-02-13
2003-08-12
Jeanglaude, Jean Bruner (Department: 2819)
Coded data generation or conversion
Digital code to digital code converters
Unnecessary data suppression
C341S106000, C341S050000
Reexamination Certificate
active
06606040
ABSTRACT:
BACKGROUND OF THE INVENTION
Data compression refers to the process of reducing the amount of data needed to represent a given information. The underlying basis of the reduction process is the removal of redundant or unnecessary data. Data compression techniques reduce the costs for information storage and transmission. Data compression techniques are used in many applications, ranging from simple file size reduction to speech and video encoding.
There are two different types of compression: lossless and lossy. In lossless compression, the source message at the encoder input is retrieved exactly at the output of the decoder. In lossy compression, the message is not retrieved exactly, but the information loss is tolerable for the type of application targeted by the compression schemes. Lossy compression is mainly used for speech, audio, image and video signals. The aim of the compression algorithm is to represent the signal with a minimum number of bits while maintaining the signal intelligibility and perceptual quality. All the information that cannot be perceived by human sensors can be removed.
Lossless compression techniques are used in applications where no information loss is tolerable such as compressing executable and source code files, satellite imaging and medical imaging. The techniques are also used as part of lossy compression schemes for better compression ratios.
One well-known technique for performing lossless compression is the LZW Lempel-Ziv-Welch (“LZW”) algorithm. The LZW algorithm is a universal algorithm based on string parsing according to a fixed rule. It is based on the concept that often used sequences can be encoded in a lesser number of bits than would be required to spell out the entire sequence. The LZW algorithm requires the initialization of a table with the alphabet of the source. A symbol width is selected and the source alphabet is created for the symbols and stored in a coding table in the encoder and the decoder before the start of the encoding process. The LZW algorithm adds selected sequences of symbols (vocabulary) to a dictionary as it encodes received sequences of symbols. Sequences contained in the dictionary can be encoded with a lesser number of bits than that required to spell out the entire sequence with symbols. The size of the source alphabet is dependent on the width of the symbol. For example, a symbol width of 1 byte (8 bits) requires a source alphabet of 28 (256) entries and a symbol width of 2 bytes (16 bits) requires a source alphabet of 216 (64K) entries. Typically, the LZW algorithm is implemented with a symbol width of one byte (8 bits). The LZW algorithm searches the coding table for the longest match in a received sequence of symbols and transmits the index of the longest match stored in the dictionary.
FIG. 1
illustrates a prior art LZW coding table
100
in an encoder and decoder for performing lossless data compression. The LZW coding table
100
can be a ternary Contents Addressable Memory (“CAM”). The input sequence of symbols
102
is translated to a sequence of indexes by the encoder using the source alphabet
106
and dictionary
108
stored in the LZW coding table
100
. The coding table
100
in the encoder
110
and the decoding table
120
in decoder
112
include the source alphabet
106
and dictionary
108
. The sequence of indexes
114
is transmitted by the encoder
110
and decoded by the decoder
112
. The decoder
112
provides an output string
104
with the same symbols as the input sequence of symbols
102
. The source alphabet
106
is stored in the LZW coding table
100
in the encoder
110
and the decoder
112
before the encoder
110
starts to encode the input sequence of symbols
102
. The sequence of indexes
114
transmitted from the encoder
110
to the decoder
112
are indexes of plain text symbols stored in the source alphabet
106
or indexes of strings of symbols stored in the dictionary
108
. The encoder
110
and the decoder
112
independently create entries in their respective dictionaries by learning new sequences of symbols dependent on the initial source alphabet. The encoder
110
adds a new sequence of symbols in the dictionary but transmits the index of the previously learned symbols or sequence of symbols to the decoder
112
in the sequence of indexes
114
. The decoder also learns the new sequence of symbols and stores the new sequence of symbols at a new index in the LZW decoding table
120
in the dictionary
108
.
FIG. 2
illustrates a prior art LZW compression of an input string in the encoder
110
shown in FIG.
1
. The source alphabet
106
(
FIG. 1
) is stored in the LZW coding table
100
(
FIG. 1
) before the encoder
110
(
FIG. 1
) starts parsing the input sequence of symbols
102
or before the decoder starts decoding. The source alphabet
106
(
FIG. 1
) for an 8-bit symbol is stored at indexes 0-255 in the coding table
100
(
FIG. 1
) and the decoding table
120
(FIG.
1
). The contents of five of the 256 locations in the source alphabet
106
(
FIG. 1
) are shown. Symbol ‘/’ is stored at index
47
, symbol ‘b’ is stored at index
98
, symbol ‘d’ is stored at index
100
, symbol ‘e’ is stored at index
101
, symbol ‘t’ is stored at index
116
and symbol ‘w’ is stored at index
119
. An additional entry
256
at index
256
in the source alphabet
106
in the LZW coding table
100
stores End Of String (“EOS”), and entry
257
at index
257
in the dictionary
108
in the LZW coding table
100
stores a Flush code.
An input sequence of symbols
102
is received by the encoder
110
(FIG.
1
). The encoder
110
(
FIG. 1
) parses the input sequence of symbols
102
and transmits the sequence of indexes
114
(
FIG. 1
). The input sequence of symbols
102
is encoded by the encoder
110
(
FIG. 1
) by parsing the input sequence of symbols
102
and searching the LZW coding table
100
for the longest match for the symbols and transmitted as a sequence of indexes (code words) for entries in the LZW coding table
100
. An index can be a pointer to an entry in the source alphabet
106
or the dictionary
108
.
As shown in the LZW coding table
100
, the index for the entry in the source alphabet
106
storing the symbol ‘/’ is
47
. Initially, the coding table
100
stores only the source alphabet
106
. As a sequence of symbols
102
is received by the encoder
110
(FIG.
1
), the encoder
110
(
FIG. 1
) parses the sequence of symbols
102
dependent on the symbol width. The encoder
110
(
FIG. 1
) selects a symbol in the sequence of symbols
102
(
FIG. 1
) and searches the LZW coding table
100
for the symbol. The encoder learns vocabulary by concatenating known symbols and sequences of symbols. If the symbol is found, the symbol is concatenated with the next symbol, and the LZW coding table
100
is searched for a sequence of symbols formed by the two symbols. If the sequence of symbols is not stored in the LZW coding table
100
, the index of the previously identified symbol or sequence of symbols is transmitted and the new sequence of symbols is added to the LZW coding table
100
.
The operation of the encoder using the LZW algorithm is illustrated using the input sequence of symbols
102
: /wed/we/wee/web/wet/ as shown in
FIG. 2 and a
symbol width of one character (8 bits). The coding table
100
stores the initial alphabet which includes an entry for each 8-bit symbol including ‘/’, ‘w’, ‘e’, ‘d’, ‘b’ and ‘t’. The parsing of the input sequence of symbols
102
starts with symbol ‘/’. Symbol ‘/’ is stored in the LZW coding table
100
at index
47
, ‘/’ is concatenated with the next symbol ‘w’, and the coding table is searched for the sequence of symbols ‘/w’; since ‘/w’ is not then stored in the LZW coding table
100
, ‘/w’ is learned by storing ‘/w’ at the next sequential index
258
. The index for ‘/’; that is,
47
the previously identified symbol is transmitted in the sequence of indexes
104
.
Parsing starts again at symbol ‘w’ in the input sequence of symbols
102
. The LZW coding table
100
is searched for symbol ‘w’. Symbol ‘w’ is
Hamilton Brook Smith & Reynolds P.C.
Jeanglaude Jean Bruner
Mosaid Technologies Inc.
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