Image analysis – Image compression or coding – Adaptive coding
Reexamination Certificate
2000-12-04
2004-10-12
Ahmed, Samir (Department: 2621)
Image analysis
Image compression or coding
Adaptive coding
C358S426020, C341S051000, C375S240020, C348S404100
Reexamination Certificate
active
06804401
ABSTRACT:
In digital systems, image format documents are often compressed to save storage costs or to reduce transmission time through a transmission channel. Lossless compression can be applied to these documents that can achieve very good compression on regions of the document that are computer rendered such as characters and graphics. However, areas of the document that contain scanned image data will not compress well. Lossy compression technologies such as JPEG can be applied to the document that will work well on scanned, continuous tone, areas of the document. Image quality problems arise with this compression technology, and with transform-coding technologies in general, at high contrast edges that are produced by computer rendered objects. A solution to this problem is to apply different compression technologies to the document to optimize image quality and compressibility. This leads to a greater challenge of managing and controlling the multiple compression technologies so as to achieve guaranteed compression rates.
U.S. Pat. No. 5,479,587 discloses a print buffer minimization method in which raster data is compressed by trying different compression procedures with increasing compression ratios until the raster data is compressed sufficiently to fit into a print buffer. Each time, a compression procedure with a higher compression ratio is selected from a predefined repertoire of such procedures, ranging from lossless procedures, such as run-length encoding, to lossy procedures such as JPEG. Generally, lossless encoding is effective for text and line art data while lossy encoding is effective on image data. However, lossy compression methods may produce poor print quality when the nature of the raster page calls for lossy compression in order to achieve a predetermined compression ratio. This is because only one of the selected compression procedures is summarily applied across each strip of the page. When a strip contains both image data as well as text or line art data, a lossy compression procedure will generally blur sharp lines that usually delineate text or line art data or may introduce other undesirable artifacts.
U.S. patent application Ser. No. 09/727.821 by Zeck et al. filed Dec. 04, 2000 describes a compression system in which plural image data blocks in a strip of data blocks are analyzed based on their content to determine which data types are present in each block. Subsequent to the analysis step, each block is assigned to a compression method that is optimal for its data type. Control of image quality and compression rate is thereby provided. This control is based on a priori optimizations and tradeoffs, with no mechanism to address achievement of “guaranteed” or required compression constraints.
The references described herein and above are incorporated by reference for their teachings.
SUMMARY OF THE INVENTION
A method for digital image compression of a raster image uses different compression methods for selected parts of the image and dynamically adjusts compression and segmentation parameters to control tradeoff of image quality and compression. The image is encoded into a single data stream for efficient handling by disk, memory and I/O systems.
In accordance with one aspect of the invention, there is provided a method of compressing a received document, comprising: receiving a document containing unknown combinations of a plural data types; determining a required compression amount for the document, compressing portions of the document with a compression method selected to meet a local compression constraint or set of constraints; comparing actual compression with said local compression constraint; and iteratively compressing portions of the document with progressively more aggressive compression techniques to meet said local compression constraint. The method may also provide for comparing actual compression of the document with a global compression constraint or set of global constraints; and iteratively compressing said document with progressively more aggressive compression techniques to meet said global compression constraint.
In accordance with another aspect of the invention, there is provided a compression system comprising: a document input, receiving documents containing unknown combinations of a plural data types; plural document compression systems, lossy compression and lossless compression; a compression comparison arrangement, comparing compressed document information with compression constraints to determine whether an amount of compression applied to a document meets compression constraint requirements; a feedback arrangement, controlling selection of said plural document compression devices to increase compression applied to documents to meet compression restraint requirements and an iterative compression processor, iteratively processing documents, responsive to said feedback arrangement.
The inventive system is in the stable feedback loop that manages to a fine granularity (typically 8×8 pixel blocks) the compression of image data so as to be compliant with a plurality of compression constraints; management of an incremental bias toward more aggressive compression that selectively applies more aggressive compression methods to blocks that are most tolerant with respect to visible artifacts; and adjustable segmentation and compression parameters used to control image compression. The components of the system include: processing of compression rate information so as to determine appropriate feedback signals to the segmenter; and a segmenter that is capable of responding to these feedback signals so as to progressively increase the bias toward more aggressive compression.
REFERENCES:
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patent: 5812700 (1998-09-01), Fang et al.
patent: 5915079 (1999-06-01), Vondran et al.
patent: 6031939 (2000-02-01), Gilbert et al.
patent: 6330363 (2001-12-01), Accad
patent: 6356660 (2002-03-01), Shannon
D'Ortenzio Remo J.
Nelson William E.
Sweet James M.
Ahmed Samir
Bhatnagar Anand
Costello Mark
Wait Christopher D.
Xerox Corporation
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