JOURNAL ARTICLE

Transform-Domain Rate-Distortion Optimization Accelerator For H.264/Avc Video Encoding

Sarwer, Mohammed GolamPo, Lai ManGuo, KaiQ.M. Jonathan Wu

Year: 2009 Journal:   Zenodo (CERN European Organization for Nuclear Research)   Publisher: European Organization for Nuclear Research

Abstract

In H.264/AVC video encoding, rate-distortion optimization for mode selection plays a significant role to achieve outstanding performance in compression efficiency and video quality. However, this mode selection process also makes the encoding process extremely complex, especially in the computation of the ratedistortion cost function, which includes the computations of the sum of squared difference (SSD) between the original and reconstructed image blocks and context-based entropy coding of the block. In this paper, a transform-domain rate-distortion optimization accelerator based on fast SSD (FSSD) and VLC-based rate estimation algorithm is proposed. This algorithm could significantly simplify the hardware architecture for the rate-distortion cost computation with only ignorable performance degradation. An efficient hardware structure for implementing the proposed transform-domain rate-distortion optimization accelerator is also proposed. Simulation results demonstrated that the proposed algorithm reduces about 47% of total encoding time with negligible degradation of coding performance. The proposed method can be easily applied to many mobile video application areas such as a digital camera and a DMB (Digital Multimedia Broadcasting) phone.

Keywords:
Rate–distortion optimization Computation Entropy encoding Encoding (memory) Coding (social sciences) Data compression Frame rate Entropy (arrow of time) Process (computing) Hardware acceleration

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Topics

Video Coding and Compression Technologies
Physical Sciences →  Computer Science →  Signal Processing
Image and Video Quality Assessment
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Data Compression Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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