Abstract
Symmetry considerations play a key role in modern science, and any differentiable symmetry of the action of a physical system has a corresponding conservation law. Symmetry may be regarded as reduction of Entropy. This work focuses on reducing the computational complexity of modern video coding standards by using the maximum entropy principle. The high computational complexity of the coding unit (CU) size decision in modern video coding standards is a critical challenge for real-time applications. This problem is solved in a novel approach considering CU termination, skip, and normal decisions as three-class making problems. The maximum entropy model (MEM) is formulated to the CU size decision problem, which can optimize the conditional entropy; the improved iterative scaling (IIS) algorithm is used to solve this optimization problem. The classification features consist of the spatio-temporal information of the CU, including the rate–distortion (RD) cost, coded block flag (CBF), and depth. For the case analysis, the proposed method is based on High Efficiency Video Coding (H.265/HEVC) standards. The experimental results demonstrate that the proposed method can reduce the computational complexity of the H.265/HEVC encoder significantly. Compared with the H.265/HEVC reference model, the proposed method can reduce the average encoding time by 53.27% and 56.36% under low delay and random access configurations, while Bjontegaard Delta Bit Rates (BD-BRs) are 0.72% and 0.93% on average.
Highlights
With the rapid development of the Internet, high-resolution video applications are very broad and a variety of different video applications have emerged
Ref. [24] presents a new CU size decision framework in parallel to reduce the complexity of the H.265/HEVC encoder, and a many-core platform is developed to speed up the coding unit tree decision
The simulation platform is based on the H.265/HEVC reference software (HM16.0), and file configurations are based on low delay (LD) and random access (RA) [32]
Summary
With the rapid development of the Internet, high-resolution video applications are very broad and a variety of different video applications have emerged. This work focuses on reducing the computational complexity of modern video encoders by using statistical redundancies. The spatial redundancies [2,3], spatio-temporal redundancies [4,5], and visual redundancies [6] were used to reduce the computational complexity of the modern video encoder. In order to achieve the trade-off between the computational complexity and encoding efficiency of the modern video encoder, the maximum-entropy-model-based coding unit (CU) size decision algorithm is proposed to reduce the computational complexity. In this work, the proposed algorithm is designed to reduce the computational complexity of the H.265/HEVC encoder. A fast CU size decision algorithm is proposed to reduce the complexity of the modern video encoder, which consists of CU termination, skip, and normal decisions.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
