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Hybrid Laplace Distribution-Based Low Complexity Rate-Distortion Optimized Quantization.

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    This study introduces a low-complexity Rate Distortion Optimized Quantization (RDOQ) method for High-Efficiency Video Coding (HEVC). The new RDOQ scheme significantly reduces encoding time while maintaining high video quality.

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    Area of Science:

    • Video Compression
    • Digital Signal Processing
    • Information Theory

    Background:

    • Rate Distortion Optimized Quantization (RDOQ) is crucial for High-Efficiency Video Coding (HEVC) performance.
    • RDOQ's high computational complexity stems from multi-stage rate-distortion minimization.
    • Existing RDOQ methods require significant processing time for optimal coefficient selection.

    Purpose of the Study:

    • To develop a computationally efficient RDOQ algorithm for HEVC.
    • To reduce the complexity of RDOQ without substantial performance degradation.
    • To accelerate the quantization process in HEVC video encoding.

    Main Methods:

    • Modeling transform coefficient statistics using a hybrid Laplace distribution.
    • Developing block-level rate and distortion models based on coefficient distribution.
    • Directly optimizing quantization levels for entire blocks to avoid complex calculations.

    Main Results:

    • Achieved approximately 70% reduction in quantization time.
    • Demonstrated up to 17% overall encoding time reduction.
    • Showcased minimal Rate-Distortion performance degradation (0.3%-0.4%).

    Conclusions:

    • The proposed low-complexity RDOQ scheme effectively reduces computational cost in HEVC.
    • This method offers a practical solution for faster video encoding.
    • The hybrid Laplace distribution model provides an efficient alternative for RDOQ optimization.