INTRA video coding is essential for high quality mobile video communication and industrial video applications since it enhances video quality, prevents error propagation, and facilitates random access. The latest high-efficiency video coding (HEVC) standard has adopted flexible quad-tree-based block structure and complex angular INTRA prediction to improve the coding efficiency. However, these technologies increase the coding complexity significantly, which consumes large hardware resources, computing time and power cost, and is an obstacle for real-time video applications. To reduce the coding complexity and save power cost, we propose a fast INTRA coding unit (CU) depth decision method based on statistical modeling and correlation analyses. First, we analyze the spatial CU depth correlation with different textures and present effective strategies to predict the most probable depth range based on the spatial correlation among CUs. Since the spatial correlation may fail for image boundary and transitional areas between textural and smooth areas, we then present a statistical model-based CU decision approach in which adaptive early termination thresholds are determined and updated based on the rate-distortion (RD) cost distribution, video content, and quantization parameters (QPs). Experimental results show that the proposed method can reduce the complexity by about 56.76% and 55.61% on average for various sequences and configurations; meanwhile, the RD degradation is negligible.
- Coding unit (CU)
- High-efficiency video coding (HEVC)
- Low complexity
- Power efficient
- Spatial correlation