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Bitplane Image Coding With Parallel Coefficient Processing.

Francesc Auli-Llinas, Pablo Enfedaque, Juan C Moure

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |October 7, 2015
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    Summary
    This summary is machine-generated.

    This study introduces Bitplane Image Coding with Parallel Coefficient (BPC-PaCo) processing, enabling efficient image coding on modern SIMD processors. BPC-PaCo achieves near-traditional performance while leveraging parallel processing for faster image compression.

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    Area of Science:

    • Computer Vision
    • Image Processing
    • Parallel Computing

    Background:

    • Traditional image coding systems are designed for Multiple Instruction, Multiple Data (MIMD) architectures, often using sequential bitplane coding.
    • Modern accelerators utilize Single Instruction, Multiple Data (SIMD) principles, posing challenges for existing sequential image coding methods.
    • Current bitplane coding strategies are not optimized for SIMD processors, limiting their efficiency.

    Purpose of the Study:

    • To develop a novel bitplane image coding method optimized for SIMD processors.
    • To enable parallel processing of image coefficients within codeblocks on SIMD architectures.
    • To minimize coding performance loss compared to traditional MIMD-based approaches.

    Main Methods:

    • Re-formulation of scanning order, context formation, probability model, and arithmetic coder for parallel processing.
    • Development of Bitplane Image Coding with Parallel Coefficient (BPC-PaCo) processing.
    • Implementation of synchronous parallel coefficient processing within codeblocks.

    Main Results:

    • BPC-PaCo effectively processes multiple coefficients in parallel and synchronously on SIMD architectures.
    • Experimental results show negligible coding performance penalties compared to traditional sequential strategies.
    • The proposed method successfully adapts bitplane coding for modern parallel processing accelerators.

    Conclusions:

    • BPC-PaCo offers an efficient solution for image coding on SIMD processors.
    • The method achieves high performance with minimal impact on compression efficiency.
    • This work bridges the gap between traditional image coding and modern parallel computing architectures.