Inter Prediction Complexity Reduction for HEVC based on Residuals Characteristics
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2016, Vol 7, Issue 10
Abstract
High Efficiency Video Coding (HEVC) or H.265 is currently the latest standard in video coding. While this new standard promises improved performance over the previous H.264/AVC standard, the complexity has drastically increased due to the various new improved tools added. The splitting of the 64x64 Largest Coding Unit (LCU) into smaller CU sizes forming a quad tree structure involves a significant number of operations and comparisons which imposes a high computational burden on the encoder. In addition, the improved Motion Estimation (ME) techniques used in HEVC inter prediction in order to ensure greater compression also contribute to the high encoding time. In this paper, a set of standard thresholds are identified based on the Mean Square (MS) of the residuals. These thresholds are used to terminate the CU splitting process and to skip some of the inter modes processing. In addition, CUs with large MS values are split at a very early stage. Experimental results show that the proposed method can effectively reduce the encoding time by 62.2% (70.8% for ME) on average, compared to HM 10, yielding a BD-Rate of only 1.14%.
Authors and Affiliations
Kanayah Saurty, Pierre Catherine, Krishnaraj Soyjaudah
Performance Evaluation of SIFT and Convolutional Neural Network for Image Retrieval
Convolutional Neural Network (NN) has gained a lot of attention of the researchers due to its high accuracy in classification and feature learning. In this paper, we evaluated the performance of CNN used as feature for i...
Robust Video Content Authentication using Video Binary Pattern and Extreme Learning Machine
Recently, due to easy accessibility of smartphones, digital cameras and other video recording devices, a radical enhancement has been experienced in the field of digital video technology. Digital videos have become very...
An Incremental Technique of Improving Translation
Statistical machine translation (SMT) refers to using probabilistic methods of learning translation process primarily from the parallel text. In SMT, the linguistic information such as morphology and syntax can be added...
Mitigation of Cascading Failures with Link Weight Control
Cascading failures are crucial issues for the study of survivability and resilience of our infrastructures and have attracted much interest in complex networks research. In this paper, we study the overload-based cascadi...
Optimal Pragmatic Clustering for Wireless Networks
Nodes’ clustering in wireless networks is one of the solutions that used to improve network performance. This paper discusses the clustering in wireless networks. Then it presents a novel clustering algorithm named Pragm...