Maximum-Entropy-Model-Enabled Complexity Reduction Algorithm in Modern Video Coding Standards

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.

Scrutiny of a More Flexible Counterpart of Huang–Kotz FGM’s Distributions in the Perspective of Some Information Measures

“…One way to think about entropy reduction is through symmetry (cf. [17]). The differential entropy, often known as the corresponding measure for a continuous RV X with a PDF f X (x), and CDF F X (x), is defined by (cf.…”

Homeland security video surveillance system utilising the internet of video things for smart cities

“…Video surveillance cameras are one of the most important applications of IoT devices that generate a huge amount of data used in multimedia data storage and transmission in smart cities. Some many techniques and algorithms are used to achieve a high quality of video compression and coding in real-time video surveillance cameras [14,15]. Most of the proposed H.265/ HEVC encoders in the literature are focusing on achieving high performance, better quality, low complexity and configurable architecture.…”

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