Image analysis – Image compression or coding – Including details of decompression
Reexamination Certificate
1999-12-17
2004-08-17
Mehta, Bhavesh M. (Department: 2625)
Image analysis
Image compression or coding
Including details of decompression
C382S248000, C382S250000, C382S251000, C358S426160, C375S240180, C375S240200
Reexamination Certificate
active
06778707
ABSTRACT:
BACKGROUND OF THE INVENTION AND MATERIAL DISCLOSURE STATEMENT
The transmission of electronic data via facsimile machines and similar devices has become quite common. Efforts to transmit significantly larger volumes of this data within a substantially shortened period of time are constantly being made. This is true not only to allow for data to be sent from one location to another at faster speeds and thereby causing less inconvenience to the user, but to enable more complex data to be transmitted between the same locations without drastically increasing the required processing time. For example the facsimile processing time for a detailed halftoned image will be many times more than that of a simple sheet of black text on a white page when using the same fax machine. By the same token, fax processing of a color image will require an even greater amount of time than its greatly detailed halftoned counterpart.
Without any form of processing reduction, color image data files via facsimile would require extensive resources—very large buffers for one example—and would still take a great deal of processing time, thereby causing receipt of such transmission to become very lengthy and expensive and therefore, impractical. The transmission of color image data via fax is typically accomplished using some form of data compression prior to transmission. The JPEG (Joint Photographic Experts Group) standard provides a well known method of compressing electronic data. JPEG uses the discrete cosine transform (DCT) to map space data into spatial frequency domain data. Simply put, the first step in JPEG compression is to transform an 8×8 block of pixels into a set of 8×8 coefficients using the DCT. In a block, the DCT coefficient with the lowest frequency is referred to as the DC coefficient (DCC), and the remaining coefficients are AC coefficients (ACCs). The DCC and ACCs are quantized—divided by an integer referred to as the “step size” and rounded to the nearest whole number. The losses that occur during JPEG compression typically occur during the quantization step. The magnitude of this loss is obviously dependent upon the step size selected and the resulting amount of round-off required to perform quantization.
Next, the quantized coefficients are arranged in a one dimensional vector by following a selected path (i.e. zigzag) through the 8×8 block of quantized coefficients. The DCC is typically the first value in the vector. Ordinary JPEG compression typically includes replacing the quantized DCC with the difference of its actual value minus the DCC of the previous block, to provide a differential DCC. Finally, the vector is encoded into a bit stream through a sequence of Run Length Counting (RLC) operations, combined with Variable Length Codes (VLC) to produce a compressed data stream.
The “receiving” portion of a fax transmission, after storage of the incoming data in a buffer, applies the inverse of the JPEG operations utilized in the sending portion. First, VLD/RLD decoding operations are performed to decompress the data stream, followed by a inverse DC DPCM operation to recover the DC component of the coefficient matrix. The resulting serial data is then arranged in a 8×8 matrix using the inverse zig-zag pattern. An inverse quantization is then performed. That result is then subjected to an inverse 8×8 discrete cosine transformation to yield the output image. Considerable processing time must be budgeted for the inverse 8×8 discrete cosine transform.
Color image data is complex, so high compression ratios must usually be applied in order to complete the transmission within an acceptable time frame. High compression ratios lead to more data loss, which typically occurs at the higher end of the frequency range. Further, the imaging devices typically included with fax machines in the lower end of the market usually include thermal ink-jet printers and would likely use error diffusion halftoning techniques. The halftoning that occurs when using a thermal ink jet printer results in an additional loss of high frequency data. Thus, much of the detail in the original image that is preserved and transmitted will never actually be viewed by the ultimate user.
With this in mind, successful fax transmission requires a proper correspondence between the decompression operation being applied to the image data and the clock speed of CPU of the receiving fax. In other words, if the decompression operation requires to much processing for a given CPU speed the data will have to wait for reception, and an appropriately sized buffer will be required. This will also frustrate the human operator if it delays the printing of a color fax too much and if the phone line wait times become to long because of buffer overflow, the transmission will be terminated. Thus, it is advantageous to reduce processing time at the receiving fax. One way to do this is obviously to implement a faster CPU to keep the data moving through the modem. Further, a larger buffer may be provided to avoid wait time in the phone line transmission. However, these solutions result in significant cost increases and may even be impractical. Thus, it is most advantageous to shorten the computational processing time of a color facsimile by implementing a faster data decompression without having to resort to the purchase of more expensive equipment.
The following disclosures may be relevant to aspects of the present invention:
U.S. Pat. No. 5,737,450 to Hajjahmad et al. issued Apr. 7, 1998 discloses a method and apparatus for applying an image filter to an image signal where image data terms, corresponding to the image signal, are converted by means of an overlapping operation and a scaled forward orthogonal transformation to form frequency coefficient matrices, the image filter is converted by means of a descaled orthogonal transformation to form a descaled frequency filter matrix, and the frequency coefficient matrices are multiplied by the descaled frequency filter matrix to form filtered coefficient matrices for conversion into a filtered image signal by means of an inverse orthogonal transformation process.
U.S. Pat. No. 5,699,170 to Yokose et al. issued Dec. 16, 1997, discloses an image communication system wherein transmission of an image between an image transmission apparatus and an image reception apparatus which include image output sections having different performances can be performed without making an inquiry for the performance prior to transmission is disclosed. An image is inputted by an image input section and sent to a hierarchization section in the image transmission apparatus. The hierarchization section converts the inputted image into hierarchic communication data and transmits hierarchized data to a selection section of the image reception apparatus. The selection section extracts only necessary data from the hierarchic communication data transmitted thereto in accordance with the performance of an image output section of the image reception section and then sends the necessary data to the image output section after, if necessary, they are converted into image data. The image output section visualize the image data transmitted thereto from the selection section.
U.S. Pat. No. 5,642,438 to Babkin issued Jun. 24, 1997 discloses image compression implementing a fast two-dimensional discrete cosine transform. More specifically, Babkin discloses a method and apparatus for the realization of two-dimensional discrete cosine transform (DCT) for an 8×8 image fragment with three levels of approximation of DCT coefficients. “JPEG: Still Image Compression Standard”, New York, N.Y., Van Nostrand Reinhold, 1993 by W. B. Pennebaker and J. L. Mitchell.
All of the references cited herein are incorporated by reference in their entirety for their teachings.
Accordingly, although known apparatus and processes are suitable for their intended purposes, a need remains for image decompression via a fast JPEG compressor using a variable block-size inverse discrete cosine transform to decompress digital
Bayat Ali
Mehta Bhavesh M.
Wait Christopher D.
Xerox Corporation
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