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      CHAPTER 3                                                                     Syntax



      The compression achieved using CCITT encoding depends on the data, as well as
      on the value of various optional parameters. For Group 3 one-dimensional
      encoding, in the best case (all zeros), each scan line compresses to 4 bytes, and the
      compression factor depends on the length of a scan line. If the scan line is 300
      bytes long, a compression ratio of approximately 75 : 1 is achieved. The worst case,
      an image of alternating ones and zeros, produces an expansion of 2 : 9.


3.3.6 JBIG2Decode Filter

      The JBIG2Decode filter (PDF 1.4) decodes monochrome (1 bit per pixel) image
      data that has been encoded using JBIG2 encoding. JBIG stands for the Joint Bi-
      Level Image Experts Group, a group within the International Organization for
      Standardization (ISO) that developed the format. JBIG2 is the second version of a
      standard originally released as JBIG1.

      JBIG2 encoding, which provides for both lossy and lossless compression, is useful
      only for monochrome images, not for color images, grayscale images, or general
      data. The algorithms used by the encoder, and the details of the format, are not
      described here. A working draft of the JBIG2 specification can be found through
      the Web site for the JBIG and JPEG (Joint Photographic Experts Group)
      committees at < http://www.jpeg.org >.

      In general, JBIG2 provides considerably better compression than the existing
      CCITT standard (discussed in Section 3.3.5). The compression it achieves
      depends strongly on the nature of the image. Images of pages containing text in
      any language compress particularly well, with typical compression ratios of 20:1
      to 50:1 for a page full of text. The JBIG2 encoder builds a table of unique symbol
      bitmaps found in the image, and other symbols found later in the image are
      matched against the table. Matching symbols are replaced by an index into the
      table, and symbols that fail to match are added to the table. The table itself is
      compressed using other means. This method results in high compression ratios
      for documents in which the same symbol is repeated often, as is typical for
      images created by scanning text pages. It also results in high compression of white
      space in the image, which does not need to be encoded because it contains no
      symbols.

      While best compression is achieved for images of text, the JBIG2 standard also
      includes algorithms for compressing regions of an image that contain dithered
      halftone images (for example, photographs).

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