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    Area of Science:

    • Video Compression and Processing
    • Computer Vision and Image Analysis
    • Digital Signal Processing

    Background:

    • 360-degree video projection creates stretched redundant data, leading to inefficient encoding and transmission.
    • Existing all-zero block (AZB) detection methods fail to account for this projection-induced redundancy.
    • Reducing computational and transmission resources is crucial for efficient 360-degree video coding.

    Purpose of the Study:

    • To develop an adaptive method for detecting redundant data in transformed blocks of 360-degree video.
    • To propose a fast 360-degree video coding scheme that leverages redundancy detection to accelerate encoding.
    • To improve the efficiency of all-zero block (AZB) detection by considering projection-specific redundancies.

    Main Methods:

    • Derived a latitude-adaptive redundancy detection (LARD) approach based on spectrum analysis to identify redundant coefficients.
    • Proposed a latitude-redundancy-aware AZB detection scheme (LRAS) with three stages: L-AZB, LG-AZB, and LP-AZB detection.
    • Developed novel latitude-adaptive models for sum of absolute difference estimation and rate-distortion optimization to enhance AZB detection accuracy.

    Main Results:

    • Achieved average total encoding time reductions of 25.85% (low-delay) and 20.38% (random access) compared to HEVC.
    • Reported minimal BDBR increases (0.16% and 0.13%) and BDPSNR loss (0.01dB), indicating preserved video quality.
    • Demonstrated significant time savings in transform and quantization stages (60.13% and 59.94% on average).

    Conclusions:

    • The proposed LRAS scheme effectively accelerates 360-degree video encoding by intelligently detecting and handling redundant data.
    • LARD and the subsequent AZB detection stages provide a robust solution for optimizing video compression efficiency.
    • The method offers a practical approach to reduce computational load and transmission resources in 360-degree video applications.