(12) United States Patent
`Fallon
`
`USOO6195024B1
`(10) Patent No.:
`US 6,195,024 B1
`(45) Date of Patent:
`Feb. 27, 2001
`
`(54) CONTENT INDEPENDENT DATA
`COMPRESSION METHOD AND SYSTEM
`
`(74) Attorney, Agent, or Firm-Frank V. DeRosa; F. Chau
`& ASSociates, LLP
`
`(75) Inventor: James J. Fallon, Bronxville, NY (US)
`(73) Assignee: Realtime Data, LLC, New York, NY
`(US)
`
`(*) Notice:
`
`Subject to any disclaimer, the term of this
`patent is extended or adjusted under 35
`U.S.C. 154(b) by 0 days.
`
`(21) Appl. No.: 09/210,491
`(22) Filed:
`Dec. 11, 1998
`9
`(51) Int. Cl." .............................. H03M 7/34; H03M 7700
`(52) U.S. Cl. ................................................. 341/51; 341/79
`(58) Field of Search .................................. 341/51, 79, 67;
`709/231, 219, 236,250; 358/1.1; 712/32;
`711/208
`
`(56)
`
`References Cited
`U.S. PATENT DOCUMENTS
`
`4,872,009
`4,929.946
`5,045,852
`5,097.261
`5,175,543
`
`10/1989 Tsukiyama et al..
`5/1990 O Brien et al. .
`9/1991 Mitchell et al. .
`3/1992 Langdon, Jr. et al..
`12/1992 Lantz ..................................... 341/S1
`(List continued on next page.)
`Primary Examiner Patrick Wamsley
`
`ABSTRACT
`(57)
`Systems and methods for providing content independent
`lossleSS data compression and decompression. A data com
`pression System includes a plurality of encoders that are
`configured to Simultaneously or Sequentially compress data
`independent of the data content. The results of the various
`encoders are compared to determine if compression is
`achieved and to determine which encoder yields the highest
`lossleSS compression ratio. The encoded data with the high
`est lossleSS compression ratio is then Selected for Subsequent
`data processing, Storage, or transmittal. A compression iden
`tification descriptor may be appended to the encoded data
`with the highest compression ratio to enable Subsequent
`decompression and data interpretation. Furthermore, a timer
`may be added to measure the time elapsed during the
`encoding process against an a priori-specified time limit.
`When the time limit expires, only the data output from those
`encoders that have completed the encoding proceSS are
`compared. The encoded data with the highest compression
`ratio is Selected for data processing, Storage, or transmittal.
`The imposed time limit ensures that the real-time or pseudo
`real-time nature of the data encoding is preserved. Buffering
`the output from each encoder allows additional encoders to
`be sequentially applied to the output of the previous encoder,
`yielding a more optimal lossless data compression ratio.
`
`34 Claims, 16 Drawing Sheets
`
`DATA STREAM
`
`
`
`
`
`
`
`
`
`
`
`
`
`ENCODERE1
`
`BUFFER
`COUNTER 1
`
`ENCODERE2 cE 2
`
`
`
`
`
`ENCODED DATA
`E.
`
`...H.S.Hoorer, P.A.C.E.
`
`COUNTER
`10-7
`
`BUFFER
`20
`
`ENCODERE3
`
`COUNTER 3 DEN DESCRIPTION
`
`
`
`ENCODEREn
`
`BUFFER
`COUNTERn
`
`30
`
`40
`
`Comcast - Exhibit 1021, page 1
`
`

`

`US 6,195,024 B1
`Page 2
`
`U.S. PATENT DOCUMENTS
`5/1993 Normile et al..
`5,212,742
`SE o9.
`s et al i
`eOSS et a
`21 - -2
`5,243,348
`9/1993 Jackson.
`5,270.832
`12/1993 Balkanski et al..
`5,379,036
`1/1995 Storer.
`5,381,145
`1/1995 Allen et al..
`5,394,534
`2/1995 Kulakowski et al. .
`5,412,384
`5/1995 Chang et al. .......................... 341/79
`5,461,679
`10/1995 Normile et al..
`5,467,087
`11/1995 Chu.
`5,471,206
`11/1995 Allen et al..
`5,479,587
`12/1995 Campbell et al..
`5,486,826
`1/1996 Remilard.
`5,495,244
`2/1996 Je-Chang et al. .
`5,533,051
`7/1996 James.
`5,583,500
`12/1996 Allen et al..
`5,627.534
`5/1997 Craft.
`5,654,703
`8/1997 Clark, II.
`5,668.737
`9/1997 Iler.
`
`5,717,393
`5,717,394
`5,729.228
`5,748,904
`5,771,340
`5,784,572
`5,799,110
`5,805,932
`5,809, 176
`5,818,368
`5,818,530
`5,819,215
`5,825,424
`5,847,762
`5,861,824
`5,917,438
`5,964.842
`5.991,515
`6.031939
`2Y- - -a-
`
`2/1998 Nakano et al. .
`2/1998 Schwartz et al. .
`3/1998 Franaszek et al..
`5/1998 Huang et al..
`6/1998 Nakazato et al..
`7/1998 Rostoker et al. .
`8/1998 Israelsen et al. .
`9/1998 Kawashima et al. .
`9/1998 Yajima.
`10/1998 Langley.
`10/1998 Canfield et al. .
`10/1998 Dobson et al..
`10/1998 Canfield et al. .
`12/1998 Canfield et al. .
`1/1999 Ryu et al..
`6/1999 Ando.
`10/1999 Packard.
`11/1999 Fall et al..
`2/2000 Gilbert et all
`e e a
`
`* cited by examiner
`
`Comcast - Exhibit 1021, page 2
`
`

`

`U.S. Patent
`
`Feb. 27, 2001
`
`Sheet 1 of 16
`
`US 6,195,024 B1
`
`
`
`INPUT DATA STREAM
`
`IDENTIFY INPUT DATA TYPE AND
`GENERATE DATA TYPE IDENTIFICATION
`SIGNAL
`
`2
`
`DATA TYPE
`D SIGNAL
`
`COMPRESS DATAN ACCORDANCE WITH
`IDENTIFIED DATA TYPE
`
`3
`
`-
`
`
`
`COMPRESSED DATA STREAM
`
`RETRIEVE DATA TYPE
`INFORMATION OF COMPRESSED
`DATA STREAM
`
`DECOMPRESS DATAN ACCORDANCE
`WITH IDENTIFIED DATA TYPE
`
`FIG. 1
`PRIOR ART
`
`Comcast - Exhibit 1021, page 3
`
`

`

`U.S. Patent
`
`Feb. 27, 2001
`
`Sheet 2 of 16
`
`US 6,195,024 B1
`
`LE RHEGIOONE
`
`€E NJEGJOONE
`
`UE (HEGIOONE
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`Comcast - Exhibit 1021, page 4
`
`

`

`U.S. Patent
`
`Feb. 27, 2001
`
`Sheet 3 of 16
`
`US 6,195,024 B1
`
`B
`
`
`
`
`
`
`
`RECEIVENTIAL
`DATA BLOCK FROM
`INPUT DATA STREAM
`
`300
`
`COUNT SIZE OF
`DATABLOCK
`
`302
`
`BUFFER DATABLOCK
`
`304
`
`COMPRESS DATA
`BLOCK WITH
`ENABLED ENCODERS
`
`BUFFERENCODED
`DATABLOCK OUTPUT
`FROMEACH
`ENCODER
`
`COUNT SIZE OF
`ENCODED DATA
`BLOCKS
`
`CALCULATE
`COMPRESSION
`RATIOS
`
`COMPARE
`COMPRESSION
`RATIOS WITH
`THRESHOLD LIMIT
`
`FIG. 3a
`
`308
`
`310
`
`312
`
`314
`
`Comcast - Exhibit 1021, page 5
`
`

`

`U.S. Patent
`
`Feb. 27, 2001
`
`Sheet 4 of 16
`
`US 6,195,024 B1
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`316
`
`IS
`COMPRESSION
`RATIO OF AT LEAST ONE
`ENCODED DATA BLOCK
`GREATER THAN
`THRESHOLD?
`
`NO
`
`SELECT ENCODED
`DATA BLOCK WITH
`GREATEST
`COMPRESSION RATIO
`
`APPEND NULL
`DESCRIPTOR TO
`UNENCODED INPUT
`DATABLOCK
`
`318
`
`APPEND
`CORRESPONDING
`DESCRIPTOR
`
`
`
`OUTPUT ENCODED
`DATABLOCKWITH
`DESCRIPTOR
`
`OUTPUT UNENCODED
`DATA BLOCK WITH
`NULL DESCRIPTOR
`
`320
`
`
`
`
`
`
`
`MORE
`DATA BLOCKS IN INPUT
`STREAM?
`
`TERMINATE DATA
`COMPRESSION
`PROCESS
`
`
`
`
`
`RECEIVE NEXT DATA
`BLOCK FROM INPUT
`STREAM
`
`
`
`330
`
`FIG. 3b
`
`Comcast - Exhibit 1021, page 6
`
`

`

`U.S. Patent
`
`Feb. 27, 2001
`
`Sheet 5 of 16
`
`US 6,195,024 B1
`
`?E RHEOLOONE
`
`UE (HECJOONE
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`Comcast - Exhibit 1021, page 7
`
`

`

`U.S. Patent
`
`Feb. 27, 2001
`
`Sheet 6 of 16
`
`US 6,195,024 B1
`
`RECEIVE INITIAL
`DATABLOCK FROM
`INPUT DATA STREAM
`
`500
`
`B
`
`COUNT SIZE OF
`DATABLOCK
`
`502
`
`BUFFER DATABLOCK
`
`504
`
`
`
`COMPRESS DATA
`BLOCK WITH
`ENABLED ENCODERS
`
`
`
`
`
`
`
`APPEND CORRESPONDING
`DESRABILITY FACTORS TO
`ENCODED DATABLOCKS
`
`BUFFERENCODED DATA
`BLOCK OUTPUT
`FROM EACHENCODER
`
`508
`
`510
`
`
`
`COUNT SIZE OF
`ENCODED DATA
`BLOCKS
`
`CALCULATE
`COMPRESSION
`RATIOS
`
`512
`
`514
`
`
`
`COMPARE COMPRESSION
`RATIOS WITH THRESHOLD
`LMIT
`
`516
`
`FIG. 5a
`
`Comcast - Exhibit 1021, page 8
`
`

`

`U.S. Patent
`
`Feb. 27, 2001
`
`Sheet 7 of 16
`
`US 6,195,024 B1
`
`A
`
`518
`
`
`
`IS
`COMPRESSION
`RATIO OF AT LEAST ONE
`ENCODED DATABLOCK
`GREATER THAN
`THRESHOLD?
`
`
`
`CALCULATE FIGURE OF
`MERT FOREACHENCODED
`DATA BLOCK WHICH EXCEED
`THRESHOLD
`
`APPEND NULL
`DESCRIPTOR TO
`UNENCODED INPUT
`DATABLOCK
`
`520
`
`SELECT ENCODED DATA
`BLOCKWITH GREATEST
`FIGURE OF MERIT
`
`APPEND
`CORRESPONDING
`DESCRIPTOR
`
`
`
`
`
`
`
`OUTPUT UNENCODED
`DATA BLOCKWITH
`NULL DESCRIPTOR
`
`522
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`OUTPUT ENCODED
`DATA BLOCK WITH
`DESCRIPTOR
`
`
`
`
`
`MORE
`DATA BLOCKS IN
`INPUT STREAM?
`
`YES
`
`
`
`TERMINATE DATA
`COMPRESSION
`PROCESS
`
`RECEIVE NEXT DATA
`BLOCK FROM INPUT
`STREAM
`
`534
`
`B.
`
`F.G. 5b
`
`Comcast - Exhibit 1021, page 9
`
`

`

`US. Patent
`
`Feb. 27, 2001
`
`Sheet 8 0f 16
`
`US 6,195,024 B1
`
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`Comcast - Exhibit 1021, page 10
`
`Comcast - Exhibit 1021, page 10
`
`
`
`
`
`
`

`

`U.S. Patent
`
`Feb. 27, 2001
`
`Sheet 9 of 16
`
`US 6,195,024 B1
`
`7OO
`
`INPUT INITIAL
`DATA BLOCK FROM
`INPUT DATA STREAM
`
`702
`B
`
`COUNT SIZE OF
`DATABLOCK
`
`704
`
`BUFFER DATABLOCK
`
`7O6
`
`NITALIZE TIMER
`
`708
`
`
`
`
`
`
`
`
`
`
`
`
`
`BEGIN
`COMPRESSING
`DATA BLOCK WITH
`ENCODERS
`
`710
`
`TIME EXPRED2
`
`NO
`
`
`
`NO
`
`ENCODING
`COMPLETEP
`
`STOP
`ENCODING
`PROCESS
`
`BUFFER
`ESSEE
`FROMEACH
`
`ENCODER
`
`718
`BUFFERENCODED
`DATA BLOCK FOREACH
`ENCODER THAT
`COMPLETED ENCODING
`PROCESS
`WITHIN TIME LIMIT
`
`
`
`
`
`
`
`COUNT SIZE OF
`ENCODED DATA
`BLOCKS
`
`720
`
`CALCULATE
`COMPRESSION
`RATIOS
`
`
`
`722
`
`
`
`
`
`
`
`FIG. 7a
`
`COMPARE COMPRESSION
`RATIOS WITH THRESHOLD
`LIMIT
`
`724
`
`Comcast - Exhibit 1021, page 11
`
`

`

`U.S. Patent
`
`Feb. 27, 2001
`
`Sheet 10 of 16
`
`US 6,195,024 B1
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`726
`
`IS
`COMPRESSION
`RATIO OF AT LEAST ONE
`ENCODED DATA BLOCK
`GREATER THAN
`THRESHOLD?
`
`NO
`
`SELECT ENCODED
`DATABLOCKWITH
`GREATEST
`COMPRESSION RATIO
`
`APPEND NULL
`DESCRIPTOR TO
`UNENCODED INPUT
`DATA BLOCK
`
`728
`
`APPEND
`CORRESPONDING
`DESCRIPTOR
`
`OUTPUT ENCODED
`DATA BLOCK WITH
`DESCRIPTOR
`
`OUTPUT UNENCODED
`DATABLOCKWITH
`NULL DESCRIPTOR
`
`730
`
`
`
`
`
`
`
`MORE
`DATABLOCKS IN INPUT
`STREAM?
`
`TERMINATE DATA
`COMPRESSION
`PROCESS
`
`
`
`
`
`RECEIVE NEXT DATA
`BLOCK FROM INPUT
`STREAM
`
`
`
`740
`
`FIG. 7b
`
`Comcast - Exhibit 1021, page 12
`
`

`

`U.S. Patent
`
`US 6,195,024 B1
`
`
`
`\/LV/CT CECIOCNEJ
`
`ZE (HECHOONE
`
`9E (HEGIOONE
`
`
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`?JEGJOONE
`
`06
`
`Comcast - Exhibit 1021, page 13
`
`

`

`U.S. Patent
`
`Feb. 27, 2001
`
`Sheet 12 of 16
`
`US 6,195,024 B1
`
`09
`
`
`
`
`
`
`
`
`
`L'uu E
`
`O09
`
`
`
`SèJO LOW-H
`
`06
`
`Comcast - Exhibit 1021, page 14
`
`

`

`U.S. Patent
`
`Feb. 27, 2001
`
`Sheet 13 of 16
`
`US 6,195,024 B1
`
`100
`
`102
`
`RECEIVE INITIAL
`DATA BLOCK FROM
`INPUT DATA STREAM
`
`COUNT SIZE OF
`DATABLOCK
`
`
`
`104
`
`BUFFER DATA
`BLOCK
`
`106
`
`NTIALIZE TIMER
`
`108
`
`APPLY INPUT DATA
`BLOCK TO FIRST
`ENCODING STAGE
`IN CASCADED
`ENCODER PATHS
`
`
`
`-110
`
`TIME EXPRED?
`
`116
`
`NO
`
`112 YES
`
`ENCODING
`STAGE
`COMPLETET
`
`APPLY OUTPUT
`OF COMPLETED
`ENCODING
`STAGE TO NEXT
`ENCODNG
`STAGE IN
`CASCADE PATH
`
`BUFFER
`ENCODED DATA
`BLOCK OUTPUT
`FROM
`COMPLETED
`ENCODING
`STAGE
`
`
`
`
`
`
`
`
`
`STOP ENCODING
`PROCESS
`
`SELECT BUFFERED OUTPUT OF LAST
`ENCODING STAGE IN ENCODER
`CASCADE THAT COMPLETED ENCODING
`PROCESS WITHIN TIME LIMIT
`
`
`
`COUNT SIZE OF
`ENCODED DATA
`BLOCKS
`
`
`
`122
`
`CALCULATE
`COMPRESSION
`RATIOS
`
`124
`
`COMPARE COMPRESSION
`RATIOS WITH THRESHOLD/126
`LIMIT
`
`FIG 10a
`
`A
`
`Comcast - Exhibit 1021, page 15
`
`

`

`U.S. Patent
`
`Feb. 27, 2001
`
`Sheet 14 of 16
`
`US 6,195,024 B1
`
`128
`
`
`
`
`
`
`
`
`
`
`
`
`
`IS
`COMPRESSION
`RATIO OF AT LEAST ONE
`ENCODED DATABLOCK
`GREATER THAN
`THRESHOLD?
`
`
`
`CALCULATE FIGURE OF
`134\ | MERIT FOREACHENCODED
`DATA BLOCK WHICH EXCEED
`THRESHOLD
`
`APPEND NULL
`DESCRIPTOR TO
`UNENCODED INPUT
`DATA BLOCK
`
`130
`
`136
`
`
`
`
`
`
`SELECT ENCODED DATA
`BLOCK WITH GREATEST
`FIGURE OF MERIT
`
`138
`
`APPEND
`CORRESPONDING
`DESCRIPTOR
`
`
`
`OUTPUT UNENCODED
`DATA BLOCKWITH
`NULL DESCRIPTOR
`
`132
`
`140
`
`OUTPUT ENCODED
`DATA BLOCK WITH
`DESCRIPTOR
`
`142 N
`
`
`
`
`
`MORE
`DATABLOCKS IN
`INPUT STREAM?
`
`TERMINATE DATA
`COMPRESSION
`PROCESS
`
`
`
`
`
`YES
`
`RECEIVE NEXT DATA
`BLOCK FROM INPUT
`STREAM
`
`144
`
`B FIG. 10b
`
`Comcast - Exhibit 1021, page 16
`
`

`

`US. Patent
`
`Feb. 27, 2001
`
`Sheet 15 0f 16
`
`US 6,195,024 B1
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`Comcast - Exhibit 1021, page 17
`
`Comcast - Exhibit 1021, page 17
`
`
`
`
`
`

`

`U.S. Patent
`
`Feb. 27, 2001
`
`Sheet 16 of 16
`
`US 6,195,024 B1
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`RECEIVE NEXT
`DATABLOCKN
`INPUT STREAM
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`RECEIVE INITIAL
`DATABLOCK FROM
`INPUT DATA STREAM
`
`BUFFER DATA BLOCK
`
`1200
`
`1202
`
`EXTRACT DATA
`COMPRESSION TYPE
`DESCRIPTOR
`
`
`
`1204
`
`S DATA
`COMPRESSION
`TYPE DESCRIPTOR
`NULL2
`
`SELECT DECODER(S)
`CORRESPONDING TO
`DESCRIPTOR
`
`
`
`DECODE DATABLOCK USING
`SELECTED DECODER(S)
`
`OUTPUT DECODED
`DATA BLOCK
`
`MORE DATA
`BLOCKS IN INPUT
`STREAM?
`
`
`
`
`
`TERMINATE
`DECODING PROCESS
`
`1218
`
`FIG. 12
`
`1208
`
`OUTPUT
`UNDECODED
`DATABLOCK
`
`Comcast - Exhibit 1021, page 18
`
`

`

`1
`CONTENT INDEPENDENT DATA
`COMPRESSION METHOD AND SYSTEM
`
`BACKGROUND
`
`1. Technical Field
`The present invention relates generally to data compres
`Sion and decompression and, more particularly, to Systems
`and methods for providing content independent lossleSS data
`compression and decompression.
`2. Description of the Related Art
`Information may be represented in a variety of manners.
`Discrete information Such as text and numbers are easily
`represented in digital data. This type of data representation
`is known as Symbolic digital data. Symbolic digital data is
`thus an absolute representation of data Such as a letter,
`figure, character, mark, machine code, or drawing.
`Continuous information Such as Speech, music, audio,
`images and Video, frequently exists in the natural world as
`analog information. AS is well-known to those skilled in the
`art, recent advances in very large Scale integration (VLSI)
`digital computer technology have enabled both discrete and
`analog information to be represented with digital data.
`Continuous information represented as digital data is often
`referred to as diffuse data. Diffuse digital data is thus a
`representation of data that is of low information density and
`is typically not easily recognizable to humans in its native
`form.
`There are many advantages associated with digital data
`representation. For instance, digital data is more readily
`processed, Stored, and transmitted due to its inherently high
`noise immunity. In addition, the inclusion of redundancy in
`digital data representation enables error detection and/or
`correction. Error detection and/or correction capabilities are
`dependent upon the amount and type of data redundancy,
`available error detection and correction processing, and
`extent of data corruption.
`One outcome of digital data representation is the continu
`ing need for increased capacity in data processing, Storage,
`and transmittal. This is especially true for diffuse data where
`increases in fidelity and resolution create exponentially
`greater quantities of data. Data compression is widely used
`to reduce the amount of data required to process, transmit,
`or Store a given quantity of information. In general, there are
`two types of data compression techniques that may be
`utilized either Separately or jointly to encode/decode data:
`lossleSS and lossy data compression.
`LOSSy data compression techniques provide for an inexact
`representation of the original uncompressed data Such that
`the decoded (or reconstructed) data differs from the original
`unencoded/uncompressed data. LOSSy data compression is
`also known as irreversible or noisy compression. Entropy is
`defined as the quantity of information in a given set of data.
`Thus, one obvious advantage of lossy data compression is
`that the compression ratioS can be larger than the entropy
`limit, all at the expense of information content. Many lossy
`data compression techniques Seek to exploit various traits
`within the human Senses to eliminate otherwise impercep
`tible data. For example, lossy data compression of Visual
`imagery might Seek to delete information content in exceSS
`of the display resolution or contrast ratio.
`On the other hand, lossleSS data compression techniques
`provide an exact representation of the original uncom
`pressed data. Simply stated, the decoded (or reconstructed)
`data is identical to the original unencoded/uncompressed
`data. LOSSleSS data compression is also known as reversible
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`or noiseleSS compression. Thus, loSSleSS data compression
`has, as its current limit, a minimum representation defined
`by the entropy of a given data Set.
`There are various problems associated with the use of
`lossleSS compression techniques. One fundamental problem
`encountered with most lossleSS data compression techniques
`are their content sensitive behavior. This is often referred to
`as data dependency. Data dependency implies that the com
`pression ratio achieved is highly contingent upon the content
`of the data being compressed. For example, database files
`often have large unused fields and high data redundancies,
`offering the opportunity to losslessly compress data at ratioS
`of 5 to 1 or more. In contrast, concise Software programs
`have little to no data redundancy and, typically, will not
`losslessly compress better than 2 to 1.
`Another problem with lossleSS compression is that there
`are significant variations in the compression ratio obtained
`when using a Single lossleSS data compression technique for
`data Streams having different data content and data size. This
`process is known as natural variation.
`A further problem is that negative compression may occur
`when certain data compression techniques act upon many
`types of highly compressed data. Highly compressed data
`appears random and many data compression techniques will
`Substantially expand, not compress this type of data.
`For a given application, there are many factors which
`govern the applicability of various data compression tech
`niques. These factors include compression ratio, encoding
`and decoding processing requirements, encoding and decod
`ing time delays, compatibility with existing Standards, and
`implementation complexity and cost, along with the adapt
`ability and robustness to variations in input data. A direct
`relationship exists in the current art between compression
`ratio and the amount and complexity of processing required.
`One of the limiting factors in most existing prior art lossleSS
`data compression techniques is the rate at which the encod
`ing and decoding processes are performed. Hardware and
`Software implementation tradeoffs are often dictated by
`encoder and decoder complexity along with cost.
`Another problem asSociated with lossleSS compression
`methods is determining the optimal compression technique
`for a given set of input data and intended application. To
`combat this problem, there are many conventional content
`dependent techniques which may be utilized. For instance,
`filetype descriptors are typically appended to file names to
`describe the application programs that normally act upon the
`data contained within the file. In this manner data types, data
`Structures, and formats within a given file may be ascer
`tained. Fundamental problems with this content dependent
`technique are:
`(1) the extremely large number of application programs,
`Some of which do not possess published or documented
`file formats, data structures, or data type descriptors,
`(2) the ability for any data compression Supplier or
`consortium to acquire, Store, and access the vast
`amounts of data required to identify known file descrip
`tors and associated data types, data Structures, and
`formats, and
`(3) the rate at which new application programs are devel
`oped and the need to update file format data descrip
`tions accordingly.
`An alternative technique that approaches the problem of
`Selecting an appropriate lossleSS data compression technique
`is disclosed in U.S. Pat. No. 5,467,087 to Chu entitled “High
`Speed Lossless Data Compression System” (“Chu”). FIG. 1
`illustrates an embodiment of this data compression and
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`Comcast - Exhibit 1021, page 19
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`decompression technique. Data compression 1 comprises
`two phases, a data pre-compression phase 2 and a data
`compression phase 3. Data decompression 4 of a com
`pressed input data Stream is also comprised of two phases,
`a data type retrieval phase 5 and a data decompression phase
`6. During the data compression proceSS 1, the data pre
`compressor 2 accepts an uncompressed data Stream, identi
`fies the data type of the input Stream, and generates a data
`type identification Signal. The data compressor 3 Selects a
`data compression method from a preselected Set of methods
`to compress the input data Stream, with the intention of
`producing the best available compression ratio for that
`particular data type.
`There are several problems associated with the Chu
`method. One Such problem is the need to unambiguously
`identify various data types. While these might include such
`common data types as ASCII, binary, or unicode, there, in
`fact, exists abroad universe of data types that fall outside the
`three most common data types. Examples of these alternate
`data types include: Signed and unsigned integers of various
`lengths, differing types and precision of floating point
`numbers, pointers, other forms of character text, and a
`multitude of user defined data types. Additionally, data types
`may be interspersed or partially compressed, making data
`type recognition difficult and/or impractical. Another prob
`lem is that given a known data type, or mix of data types
`within a specific Set or Subset of input data, it may be
`difficult and/or impractical to predict which data encoding
`technique yields the highest compression ratio.
`Chu discloses an alternate embodiment wherein a data
`compression rate control signal is provided to adjust specific
`parameters of the Selected encoding algorithm to adjust the
`compression time for compressing data. One problem with
`this technique is that the length of time to compress a given
`Set of input data may be difficult or impractical to predict.
`Consequently, there is no guarantee that a given encoding
`algorithm or Set of encoding algorithms will perform for all
`possible combinations of input data for a Specific timing
`constraint. Another problem is that, by altering the param
`eters of the encoding process, it may be difficult and/or
`impractical to predict the resultant compression ratio.
`Other conventional techniques have been implemented to
`address the aforementioned problems. For instance, U.S.
`Pat. No. 5,243,341 to Seroussi et al. describes a class of
`Lempel–Ziv lossleSS data compression algorithms that ulti
`lize a memory based dictionary of finite size to facilitate the
`compression and decompression of data. A Second Standby
`dictionary is included comprised of those encoded data
`entries that compress the greatest amount of input data.
`When the current dictionary fills up and is reset, the standby
`dictionary becomes the current dictionary, thereby maintain
`ing a reasonable data compression ratio and freeing up
`memory for newly encoded data Strings. Multiple dictionar
`ies are employed within the same encoding technique to
`increase the lossleSS data compression ratio. This technique
`demonstrates the prior art of using multiple dictionaries
`within a single encoding process to aid in reducing the data
`dependency of a single encoding technique. One problem
`with this method is that it does not address the difficulties in
`dealing with a wide variety of data types.
`U.S. Pat. No. 5,717,393 to Nakano, et al. teaches a
`plurality of code tables Such as a high-usage code table and
`a low-usage code table in an entropy encoding unit. A
`block-Sorted last character String from a block-Sorting trans
`forming unit is the move-to-front transforming unit is trans
`formed into a move-to-front (MTF) code string. The entropy
`encoding unit Switches the code tables at a discontinuous
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`part of the MTF code string to perform entropy coding. This
`technique increases the compression rate without extending
`the block size. Nakano employs multiple code tables within
`a single entropy encoding unit to increase the lossleSS data
`compression ratio for a given block size, Somewhat reducing
`the data dependency of the encoding algorithm. Again, the
`problem with this technique is that it does not address the
`difficulties in dealing with a wide variety of data types.
`U.S. Pat. No. 5,809,176 to Yajima discloses a technique of
`dividing a native or uncompressed image data into a plu
`rality of Streams for Subsequent encoding by a plurality of
`identically functioning arithmetic encoders. This method
`demonstrates the technique of employing multiple encoders
`to reduce the time of encoding for a Single method of
`compression.
`U.S. Pat. Nos. 5,583,500 and 5,471,206 to Allen, at al.
`disclose Systems for parallel decompression of a data Stream
`comprised of multiple code words. At least two code words
`are decoded simultaneously to enhance the decoding pro
`ceSS. This technique demonstrates the prior art of utilizing
`multiple decoders to expedite the data decompression pro
`CCSS.
`U.S. Pat. No. 5,627.534 to Craft teaches a two-stage
`lossleSS compression process. A run length precompressed
`output is post processed by a Lempel–Ziv dictionary sliding
`window dictionary encoder that outputs a Succession of
`fixed length data units. This yields a relatively high-speed
`compression technique that provides a good match between
`the capabilities and idiosyncrasies of the two encoding
`techniques. This technique demonstrates the prior art of
`employing Sequential lossleSS encoders to increase the data
`compression ratio.
`U.S. Pat. No. 5,799,110 to Israelsen, et al. discloses an
`adaptive threshold technique for achieving a constant bit rate
`on a hierarchical adaptive multistage vector quantization. A
`Single compression technique is applied iteratively until the
`residual is reduced below a prespecified threshold. The
`threshold may be adapted to provide a constant bit rate
`output. If the nth Stage is reached without the residual being
`less than the threshold, a Smaller input vector is Selected.
`U.S. Pat. No. 5,819,215 to Dobson, et al. teaches a method
`of applying either lossy or lossleSS compression to achieve
`a desired Subjective level of quality to the reconstructed
`Signal. In certain embodiments this technique utilizes a
`combination of run-length and Huffman encoding to take
`advantage of other local and global Statistics. The tradeoffs
`considered in the compression process are perceptible dis
`tortion errorS versus a fixed bit rate output.
`SUMMARY OF THE INVENTION
`The present invention is directed to Systems and methods
`for providing content independent lossleSS data compression
`and decompression. In one aspect of the present invention,
`a method for providing content independent lossleSS data
`compression comprises the Steps of:
`(a) receiving as input a block of data from a stream of
`data, the data Stream comprising one of at least one data
`block and a plurality of data blocks,
`(b) counting the size of the input data block;
`(c) encoding the input data block with a plurality of
`lossleSS encoders to provide a plurality of encoded data
`blocks;
`(d) counting the size of each of the encoded data blocks;
`(e) determining a lossless data compression ratio obtained
`for each of the encoders by taking the ratio of the size
`of the encoded data block output from the encoders to
`the size of the input data block,
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`Comcast - Exhibit 1021, page 20
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`S
`(f) comparing each of the determined compression ratios
`with an a priori user Specified compression threshold;
`(g) Selecting for output the input data block and append
`ing a null data type compression descriptor to the input
`data block, if all of the encoder compression ratioS fall
`below the a priori Specified compression threshold; and
`(h) selecting for output the encoded data block having the
`highest compression ratio and appending a correspond
`ing data type compression descriptor to the Selected
`encoded data block, if at least one of the compression
`ratioS exceed the a priori Specified compression thresh
`old.
`In another aspect of the present invention, a timer is
`preferably added to measure the time elapsed during the
`encoding process against an a priori-specified time limit.
`When the time limit expires, only the data output from those
`encoders that have completed the present encoding cycle are
`compared to determine the encoded data with the highest
`compression ratio. The time limit ensures that the real-time
`or pseudo real-time nature of the data encoding is preserved.
`In another aspect of the present invention, the results from
`each encoder are buffered to allow additional encoders to be
`Sequentially applied to the output of the previous encoder,
`yielding a more optimal lossleSS data compression ratio.
`In another aspect of the present invention, a method for
`providing content independent lossleSS data decompression
`includes the Steps of receiving as input a block of data from
`a stream of data, extracting an encoding type descriptor from
`the input data block, decoding the input data block with one
`or more of a plurality of available decoders in accordance
`with the extracted encoding type descriptor, and outputting
`the decoded data block. An input data block having a null
`descriptor type extracted therefrom is output Without being
`decoded.
`Advantageously, the present invention employs a plurality
`of encoderS applying a plurality of compression techniques
`on an input data Stream So as to achieve maximum com
`pression in accordance with the real-time or pseudo real
`time data rate constraint. Thus, the output bit rate is not fixed
`and the amount, if any, of permissible data quality degra
`dation is not adaptable, but is user or data Specified.
`The present invention is realized due to recent improve
`ments in processing Speed, inclusive of dedicated analog and
`digital hardware circuits, central processing units, (and any
`hybrid combinations thereof), which, coupled with reduc
`tions in cost, are enabling of new content independent data
`compression and decompression Solutions.
`These and other aspects, features and advantages of the
`present invention will become apparent from the following
`detailed description of preferred embodiments, which is to
`be read in connection with the accompanying drawings.
`BRIEF DESCRIPTION OF THE DRAWINGS
`FIG. 1 is a block/flow diagram of a content dependent
`high-Speed lossleSS data compression and decompression
`System/method according to the prior art;
`FIG. 2 is a block diagram of a content independent data
`compression System according to one embodiment of the
`present invention;
`FIGS. 3a and 3b comprise a flow diagram of a data
`compression method according to one aspect of the present
`invention which illustrates the operation of the data com
`pression system of FIG. 2;
`FIG. 4 is a block diagram of a content independent data
`compression System according to another embodiment of the
`present invention having an enhanced metric for Selecting an
`optimal encoding technique;
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`FIGS. 5a and 5b comprise a flow diagram of a data
`compression method according to another aspect of the
`present invention which illustrates the operation of the data
`compression system of FIG. 4;
`FIG. 6 is a block diagram of a content independent data
`compression System according to another embodiment of the
`present invention having an a priori Specified timer that
`provides real-time or pseudo real-time of output data;
`FIGS. 7a and 7b comprise a flow diagram of a data
`compression method according to another aspect of the
`present invention which illustrates the operation of the data
`compression system of FIG. 6;
`FIG. 8 is a block diagram of a content independent data
`compression System according to another embodiment hav
`ing an a priori Specified timer that provides real-time or
`pseudo real-time of output data and an enhanced metric for
`Selecting an optimal encoding technique;
`FIG. 9 is a block diagram of a content independent data
`compression System according to another embodiment of the
`present invention having an encoding architecture compris
`ing a plurality of Sets of Serially-cascaded encoders,
`FIGS. 10a and 10b comprise a flow diagram of a data
`compression method according to another aspect of the
`present invention which illustrates the operation of the data
`compression system of FIG. 9;
`FIG. 11 is block diagram of a content independent data
`decompression System according to one embodiment of the
`present invention; and
`FIG. 12 is a flow diagram of a data decompression method
`according to one aspect of the present invention which
`ill