PROJECT TITLE :

Low Complexity HEVC INTRA Coding for High-Quality Mobile Video Communication

ABSTRACT:

INTRA video coding is crucial 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-potency video coding (HEVC) standard has adopted versatile quad-tree-primarily based block structure and advanced angular INTRA prediction to improve the coding efficiency. But, these technologies increase the coding complexity significantly, that consumes giant hardware resources, computing time and power cost, and is an obstacle for real-time video applications. To scale back the coding complexity and save power price, we propose a fast INTRA coding unit (CU) depth call method primarily based on Statistical Modeling and correlation analyses. First, we tend to analyze the spatial CU depth correlation with completely different textures and gift effective strategies to predict the most probable depth range based mostly on the spatial correlation among CUs. Since the spatial correlation could fail for image boundary and transitional areas between textural and swish areas, we then present a statistical model-primarily based CU decision approach in that adaptive early termination thresholds are determined and updated based on the rate-distortion (RD) price distribution, video content, and quantization parameters (QPs). Experimental results show that the proposed method can cut back the complexity by regarding 56.76% and fifty five.61% on average for various sequences and configurations; meanwhile, the RD degradation is negligible.