Efficient Block Partitioning Method for Spatial Scalable Encoding in Versatile Video Coding

The rapid increase in video consumption, further accelerated by the coronavirus disease 2019 (COVID-19) pandemic, has driven a significant rise in demand for live streaming services and video delivery across various devices, such as smartphones and tablets. Screen size and display resolution of these devices vary widely, creating the need for flexible and efficient video transmission methods. Spatial scalable coding addresses this challenge by encoding multiple resolutions within a single bitstream, allowing devices to decode the appropriate resolution without requiring separate streams. This approach reduces redundancy and improves transmission efficiency. Versatile Video Coding (VVC), the latest international video compression standard, supports spatial scalability through its multilayer profile. VVC enhances compression performance by reusing information from lower-resolution layers; however, this added complexity increases computational overhead, particularly during encoding. In this paper, we propose an efficient block partitioning method specifically designed for scalable VVC-based coding. The method exploits structural similarities between low-resolution and high-resolution encoded data to guide partitioning decisions in the high-resolution layer, thereby reducing unnecessary computations. The experimental results demonstrate that the proposed method reduces encoding time by approximately 55%, with a BD-rate increase below 3.45%. These results validate the effectiveness of the approach in accelerating scalable video encoding without compromising visual quality, making it suitable for real-time applications and environments with limited computational resources.

Block partitioning algorithm; Spatial scalable coding; Versatile Video Coding (VVC); Video coding

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