Patent Abstract:
An apparatus and method for compressing binarized images ( 90 ) comprising receiving a binarized image ( 70 ) and generating a first sequence of first code symbols ( 80 ) representing the binarized image wherein at least one row of the image is represented in run-length encoded format and encoding a portion of the first sequence of code symbols using a preliminary encoding scheme, thereby to provide a first portion of a second sequence of code symbols, and, while encoding, accumulating the frequency of at least some of the first code symbols thus far encoded ( 100 ) and generating an additional portion of the second sequence using a modified version of the code scheme such that at least one subsequent code symbol in the first sequence with a large accumulated frequency is encoded more compactly in the second portion than at least one subsequent code symbol in the first sequence with a small accumulated frequency.

Full Description:
FIELD OF THE INVENTION 
   The present invention relates to methods for compressing binarized images, generally. 
   BACKGROUND OF THE INVENTION 
   Arithmetic coding is described in: 
   Witten, I. H et al, “Arithmetic coding for data compression”, Computing Practices, Communications of the ACM, June 1987, Vol. 30(6); and 
   “Arithmetic coding and statistical modeling”, Dr. Dobb&#39;s Journal, February 1991, pp. 16-29. 
   The MR decoding scheme is described in CCITT Recommendation T.4 and T.6 for Groups 3 and 4. 
   A conventional binarizing technique is described in Foley, J. et al,  Computer Graphics: Principles and practice,  2nd Ed., Section 13.1.2, pages 568-573. 
   The disclosures of all of the above publications are hereby incorporated by reference. 
   SUMMARY OF THE INVENTION 
   The present invention seeks to provide an improved image manipulation system. 
   There is thus provided in accordance with a preferred embodiment of the present invention a method for compressing binarized images including receiving a binarized image and generating a first sequence of first code symbols representing the binarized image wherein at least one row of the image is represented in run-length encoded format, and encoding a portion of the first sequence of code symbols using a preliminary encoding scheme, thereby to provide a first portion of a second sequence of code symbols, and, while encoding, accumulating the frequency of at least some of the first code symbols thus far encoded and generating an additional portion of the second sequence using a modified version of the code scheme such that at least one subsequent code symbol in the first sequence with a large accumulated frequency is encoded more compactly in the second portion than at least one subsequent code symbol in the first sequence with a small accumulated frequency. 
   Further in accordance with a preferred embodiment of the present invention, a modified Huffman coding scheme is employed to generate the first sequence of first code symbols. 
   In accordance with another preferred embodiment of the present invention, there is provided a method for compressing binarized images including receiving a binarized image and generating a first sequence of first code symbols representing the binarized image including a representation of one row of the binarized image and a representation of differences between at least one subsequent row and at least one previous row, and encoding a portion of the first sequence of code symbols using a preliminary encoding scheme, thereby to provide a first portion of a second sequence of code symbols, and, while encoding, accumulating the frequency of at least some of the first code symbols thus far encoded and generating an additional portion of the second sequence using a modified version of the code scheme such that at least one subsequent code symbols in the first sequence with a large accumulated frequency is encoded more compactly in the second portion than at least one subsequent code symbol in the first sequence with a small accumulated frequency. 
   Further in accordance with a preferred embodiment of the present invention, the encoding scheme used to encode the first sequence of code symbols is continually modified such that code symbols in the first sequence with a large accumulated frequency are encoded more compactly in the second portion than subsequent code symbols in the first sequence with a small accumulated frequency. 
   Still further in accordance with a preferred embodiment of the present invention, a modified-read coding scheme is employed to generate the first sequence of first code symbols. 
   Further in accordance with a preferred embodiment of the present invention, a modified modified-read coding scheme is employed to generate the first sequence of first code symbols. 
   Still further in accordance with a preferred embodiment of the present invention, the method also includes binarizing a discrete level image, thereby to provide the binarized image. 
   Additionally in accordance with a preferred embodiment of the present invention, the method also includes binarizing a continuous level image, thereby to provide the binarized image. 
   Still further in accordance with a preferred embodiment of the present invention, arithmetic coding is employed to translate the accumulated frequency of at least some of the first code symbols into second code symbols. 
   There is also provided, in accordance with a preferred embodiment of the present invention, apparatus for compressing binarized images including a run-length encoder operative to receive a binarized image and to generate a first sequence of first code symbols representing the binarized image wherein at least one row of the image is represented in run-length encoded format, and an adaptive encoder operative to encode a portion of the first sequence of code symbols using a preliminary encoding scheme, thereby to provide a first portion of a second sequence of code symbols, and, while encoding, to accumulate the frequency of at least some of the first code symbols thus far encoded and to generate an additional portion of the second sequence using a modified version of the code scheme such that at least one subsequent code symbol in the first sequence with a large accumulated frequency is encoded more compactly in the second portion than at least one subsequent code symbol in the first sequence with a small accumulated frequency. 
   There is further provided, in accordance with a preferred embodiment of the present invention, apparatus for compressing binarized images including a binarized image compressor operative to receive a binarized image and to generate a first sequence of first code symbols representing the binarized image, the first sequence including a representation of one row of the binarized image and a representation of differences between at least one subsequent row and at least one previous row, and an adaptive encoder operative to encode a portion of the first sequence of code symbols using a preliminary encoding scheme, thereby to provide a first portion of a second sequence of code symbols, and, while encoding, to accumulate the frequency of at least some of the first code symbols thus far encoded and to generate an additional portion of the second sequence using a modified version of the code scheme such that at least one subsequent code symbol in the first sequence with a large accumulated frequency is encoded more compactly in the second portion than at least one subsequent code symbol in the first sequence with a small accumulated frequency. 
   Further in accordance with a preferred embodiment of the present invention, the binarized image compressor employs a modified-read coding scheme to generate the first sequence of first code symbols. 
   Still further in accordance with a preferred embodiment of the present invention, the binarized image compressor employs a modified modified-read coding scheme to generate the first sequence of first code symbols. 
   Additionally in accordance with a preferred embodiment of the present invention, the adaptive encoder employs arithmetic coding to translate the accumulated frequency of at least some of the first code symbols into second code symbols. 
   Still further in accordance with a preferred embodiment of the present invention, the encoding scheme used to encode the first sequence of code symbols is continually modified such that code symbols in the first sequence with a large accumulated frequency are encoded more compactly in the second portion than subsequent code symbols in the first sequence with a small accumulated frequency. 

   
     BRIEF DESCRIPTION OF THE DRAWINGS 
     The present invention will be understood and appreciated from the following detailed description, taken in conjunction with the drawings in which: 
       FIG. 1  is a simplified block diagram of an image manipulation system constructed and operative in accordance with a preferred embodiment of the present invention, and 
       FIG. 2  is a simplified flowchart illustrating a preferred mode of operation in which the MR code element frequency accumulation unit of  FIG. 1  processes a single MR code element in a sequence. 
   

   Attached herewith are the following appendices which aid in the understanding and appreciation of one preferred embodiment of the invention shown and described herein: 
   Appendix A is a computer listing of a preferred software embodiment of the MR coding, arithmetic coding and MR code element frequency accumulation units of  FIG. 1 , and 
   Appendix B is a computer listing of a preferred software embodiment of the arithmetic decoding, MR code frequency accumulation and MR decoding units of  FIG. 1 . 
   DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS 
   Reference is now made to  FIG. 1  which is a simplified block diagram of an image manipulation system constructed and operative in accordance with a preferred embodiment of the present invention. 
   As shown, a digital representation of an image is provided from any suitable source, such as a scanner  10  which scans a substrate such as a continuous level photograph  20 , a digital camera  30 , a fax machine  40 , an image creation workstation  50  such as a Macintosh equipped with the Adobe Photoshop software package, or a storage medium such as a hard disk  60 . The digital representation of the image may be either a continuous level image or a discrete level image such as a document or other black and white image. 
   If the digital representation of the image is not binary, the digital representation is binarized, as indicated in  FIG. 1  by image binarization block  70 , using any conventional binarizing technique such as those described in Foley J. et al,  Computer Graphics: Principles and practice,  2nd Ed., Section 13.1.2, pages 568-573. 
   The binarized image is then coded by MR coding unit  80 , using the MR coding scheme described in CCITT Recommendation T.4 and T.6 for Groups 3 or 4. 
   The MR coded binarized image generated by MR coding unit  80  then undergoes arithmetic coding in arithmetic coding unit  90 . The arithmetic coding unit  90  receives as input:
     a. the sequence of MR code elements which forms the MR coded binarized image and   b. the estimated probability of each MR code element, which is provided by an MR code element frequency accumulation unit  100 . Initially, the estimated probabilities of all MR code elements are typically taken to be equal. However, as the MR code element sequence flows into the MR code element frequency accumulation unit  100 , the estimated probabilities change based on the number of times each MR code element is encountered.   

   The sequence of MR code elements typically includes code elements of 3 types:
     a. MR control type code elements;   b. Black run length type code elements; and   c. White run length type code elements.   

   The frequency accumulation unit  100  typically receives as input each MR code element and, associated therewith, an indication of the type of that MR code element. Typically, unit  100  computes the relative code element frequency for each code element within its own code element type. 
   The arithmetic coding unit  90  may, if desired, be replaced by an entropy encoder or an adaptive Huffman encoder. If this is the case, then the arithmetic decoding unit  110 , described below, is replaced by an entropy decoder or adaptive Huffman decoder, respectively. 
   One software embodiment of arithmetic coding unit  90  is described in “Arithmetic coding and statistical modeling”, Dr. Dobb&#39;s Journal, February 1991, pp. 16-29. The above reference also provides a software embodiment of arithmetic decoding unit  110 . 
   An alternative implementation of MR code element frequency accumulation unit  100  is described below with reference to  FIG. 2 . 
   The output of the arithmetic coding unit  90  is a very compact representation of the original image which is suitable, for example, for compact storage on any suitable optical or magnetic medium and/or for rapid facsimile transmission,  105 , on conventional equipment which preferably has a error correction capability, such as the V32bis modem. 
   The compact representation of the original image is decompressed after being transmitted or after being retrieved from archival. To decompress the compact representation, the compressed data stream is fed to an arithmetic decoding unit  110  which replaces each arithmetically coded element with a corresponding MR code element according to the frequency of the arithmetically coded element. The frequency information is provided by an MR code element frequency accumulation unit  120  which is typically identical to unit  100 . Initially, the estimated probabilities of all MR code elements are typically taken to be equal. However, as the MR code element sequence flows into the MR code element frequency accumulation unit  120 , the estimated probabilities change based on the number of times each MR code element is encountered. 
   The output of the arithmetic decoding unit  110  is a sequence of MR code elements which is decoded by an MR decoding unit  130  using the MR decoding scheme described in CCITT Recommendation T.4 and T.6 for Groups 3 or 4. 
   The output of MR decoding unit  130  is a decompressed binarized image which is substantially identical to the binarized image generated by image binarization unit  70 .  FIG. 2  is a simplified flowchart illustrating a preferred mode of operation in which either of the MR code element frequency accumulation units  100  or  120  of  FIG. 1  processes a single MR code element in a sequence of MR code elements. 
   If (process  210 ) there is a decision to reset, i.e. to begin accumulating frequencies from zero, then the method advances to stage  220 . Otherwise, the method advances to stage  240 . A reset is performed, for example, if a new image is to be processed whose characteristics are thought to differ significantly from the previous image processed. 
   In process  220 , a table is allocated for each of the three MR code element types. The number of cells in each table typically exceeds the number of code elements of each type, by 1. The difference between the content of the i&#39;th cell in the table and the (i+1)th cell in the table, also termed herein “the i&#39;th interval”, is indicative of the relative frequency of the i&#39;th code element, within its code element type. 
   Since there are 92 code elements of the White Run Length type and of the Black Run Length type, the tables for these two types each typically have 93 cells. Since there are 9 code elements of the MR Control type, the table for the MR Control type typically has 10 cells. 
   PROCESS  230 : The table contents are initialized by generating equal intervals such as, typically, intervals having a length of 1. 
   PROCESS  240 : Input is received: A single MR code element from the MR code element sequence representing the image, and, associated therewith, its MR code element type, is received as input. 
   PROCESS  250 : Unit  100  allows arithmetic coder  90  to arithmetically code the current MR code element, by supplying the frequency intervals stored in the table corresponding to the current MR code element to the arithmetic coder  90 . For example, if the MR code element is of the MR_control type, the intervals stored in the MR_control table are employed. 
   Unit  120  allows the decoder  110  to arithmetically decode the current MR code element, by supplying the same information to decoder  110 . 
   PROCESS  260 : The appropriate table is updated by incrementing by 1 the contents of each cell starting from the cell following the cell corresponding to the current code element. 
   For example, if the fourth MR_control type code element is encountered, the contents of the fifth to ninth cells of the MR-control table are incremented by 1. 
   Preferably, old frequency information is given less weight than new frequency information. One implementation of this rule is: 
   PROCESS  270 : For each type t, each time N t  code elements of type t have been processed, divide the cell contents of the frequency interval table of type t, by a suitable number such as 2. Suitable N t  values are: 256 for MR control type, 2048 for black and white run length types. 
   Appendix A is a computer listing in C language, of a preferred software embodiment of the MR coding, arithmetic coding and MR code element frequency accumulation units of  FIG. 1 . 
   Appendix B is a computer listing in C language, of a preferred software embodiment of the arithmetic decoding, MR code element frequency accumulation and MR decoding units of  FIG. 1 . 
   The programs listed in Appendices A and B may be run on a conventional computer such as any UNIX computer. 
   It is appreciated that the MR coding described hereinabove may, alternatively be replaced by MMR coding or other similar coding schemes. 
   It is appreciated that the invention shown and described herein is suitable for compressing and decompressing any type of binarized image, such as binarized discrete level images or binarized continuous level images, also termed herein “halftone images”. 
   In certain applications, it may be desirable to use the compression methods shown and described herein to compress only a portion of a binarized image. For example, in medical imaging applications, the compression methods shown and described herein may be employed to generally losslessly compress the foreground of the medical image whereas the background of the medical image may be compressed using lossy techniques. 
   It is appreciated that the software components of the present invention may, if desired, be implemented in ROM (read-only memory) form. The software components may, generally, be implemented in hardware, if desired, using conventional techniques. 
   It is appreciated that the particular embodiment described in the Appendices is intended only to provide an extremely detailed disclosure of the present invention and is not intended to be limiting. 
   It is appreciated that various features of the invention which are, for clarity, described in the contexts of separate embodiments may also be provided in combination in a single embodiment. Conversely, various features of the invention which are, for brevity, described in the context of a single embodiment may also be provided separately or in any suitable subcombination. 
   It will be appreciated by persons skilled in the art that the present invention is not limited to what has been particularly shown and described hereinabove. Rather, the scope of the present invention is defined only by the claims that follow:

Technology Classification (CPC): 6