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Detecting Computer-Induced Errors in Remote-Sensing JPEG Compression Algorithms.

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Τίτλος: Detecting Computer-Induced Errors in Remote-Sensing JPEG Compression Algorithms.
Συγγραφείς: Nguyen, Cung, Redinbo, G. Robert
Πηγή: IEEE Transactions on Image Processing; Jul2006, Vol. 15 Issue 7, p1728-1739, 12p, 2 Black and White Photographs, 5 Diagrams, 2 Graphs
Θεματικοί όροι: Fault-tolerant computing, Image compression, JPEG (Image coding standard), Computer input-output equipment, Remote sensing, Computer software, Algorithms
Περίληψη: The JPEG image compression standard is very sensitive to errors. Even though it contains error resilience features, it cannot easily cope with induced errors from computer soft faults prevalent in remote-sensing applications. Hence, new fault tolerance detection methods are developed to sense the soft errors in major parts of the system while also protecting data across the boundaries where data flow from one subsystem to the other. The design goal is to guarantee no compressed or decompressed data contain computer-induced errors without detection. Detection methods are expressed at the algorithm level so that a wide range of hardware and software implementation techniques can be covered by the fault tolerance procedures while still maintaining the JPEG output format. The major subsystems to be addressed are the discrete cosine transform, quantizer, entropy coding, and packet assembly. Each error detection method is determined by the data representations within the subsystem or across the boundaries. They vary from real number parities in the DCT to bit-level residue codes in the quantizer, cyclic redundancy check parities for entropy coding, and packet assembly. The simulation results verify detection performances even across boundaries while also examining roundoff noise effects in detecting computer-induced errors in processing steps. [ABSTRACT FROM AUTHOR]
Copyright of IEEE Transactions on Image Processing is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Detecting Computer-Induced Errors in Remote-Sensing JPEG Compression Algorithms.
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  Data: <searchLink fieldCode="AR" term="%22Nguyen%2C+Cung%22">Nguyen, Cung</searchLink><br /><searchLink fieldCode="AR" term="%22Redinbo%2C+G%2E+Robert%22">Redinbo, G. Robert</searchLink>
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  Data: IEEE Transactions on Image Processing; Jul2006, Vol. 15 Issue 7, p1728-1739, 12p, 2 Black and White Photographs, 5 Diagrams, 2 Graphs
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  Data: <searchLink fieldCode="DE" term="%22Fault-tolerant+computing%22">Fault-tolerant computing</searchLink><br /><searchLink fieldCode="DE" term="%22Image+compression%22">Image compression</searchLink><br /><searchLink fieldCode="DE" term="%22JPEG+%28Image+coding+standard%29%22">JPEG (Image coding standard)</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+input-output+equipment%22">Computer input-output equipment</searchLink><br /><searchLink fieldCode="DE" term="%22Remote+sensing%22">Remote sensing</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+software%22">Computer software</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink>
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  Data: The JPEG image compression standard is very sensitive to errors. Even though it contains error resilience features, it cannot easily cope with induced errors from computer soft faults prevalent in remote-sensing applications. Hence, new fault tolerance detection methods are developed to sense the soft errors in major parts of the system while also protecting data across the boundaries where data flow from one subsystem to the other. The design goal is to guarantee no compressed or decompressed data contain computer-induced errors without detection. Detection methods are expressed at the algorithm level so that a wide range of hardware and software implementation techniques can be covered by the fault tolerance procedures while still maintaining the JPEG output format. The major subsystems to be addressed are the discrete cosine transform, quantizer, entropy coding, and packet assembly. Each error detection method is determined by the data representations within the subsystem or across the boundaries. They vary from real number parities in the DCT to bit-level residue codes in the quantizer, cyclic redundancy check parities for entropy coding, and packet assembly. The simulation results verify detection performances even across boundaries while also examining roundoff noise effects in detecting computer-induced errors in processing steps. [ABSTRACT FROM AUTHOR]
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  Label:
  Group: Ab
  Data: <i>Copyright of IEEE Transactions on Image Processing is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1109/TIP.2006.873425
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      – Code: eng
        Text: English
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        PageCount: 12
        StartPage: 1728
    Subjects:
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        Type: general
      – SubjectFull: Image compression
        Type: general
      – SubjectFull: JPEG (Image coding standard)
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      – SubjectFull: Computer input-output equipment
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      – SubjectFull: Remote sensing
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      – SubjectFull: Computer software
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      – SubjectFull: Algorithms
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              Text: Jul2006
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              Y: 2006
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