Fast adaptive early termination for mode selection in H.264/AVC standard based on x264 implementation

Jianfeng Ren; Nasser Kehtarnavaz; Madhukar Budagavi

doi:10.1117/12.767665

26 February 2008 Fast adaptive early termination for mode selection in H.264/AVC standard based on ×264 implementation

Jianfeng Ren, Nasser Kehtarnavaz, Madhukar Budagavi

Proceedings Volume 6811, Real-Time Image Processing 2008; 68110A (2008) https://doi.org/10.1117/12.767665
Event: Electronic Imaging, 2008, San Jose, California, United States

Abstract

In the H.264/AVC video coding standard, the mode decision component involves a large amount of computation. This paper presents a fast or computationally efficient mode prediction and selection approach which has the following attributes: (a) both the spatial and temporal information are used to achieve early termination using adaptive thresholds, (b) inclusion of a modulator capable of trading off computational efficiency and accuracy, (c) a homogenous region detection procedure for 8×8 blocks based on adaptive thresholds. The developed approach consists of three main steps: (1) mode prediction, (2) early termination based on adaptive thresholds, and (3) refinement by checking all the modes. In addition, in order to avoid sub-partitions into smaller block sizes for 8x8 blocks, texture information is utilized. It is shown that the developed approach leads to a computationally efficient video coding implementation as compared to the previous fast approaches. The results obtained on QCIF, CIF, and HD format video sequences based on x264 are presented to demonstrate the computational efficiency of the developed approach at the expense of acceptably low losses in video quality.

Citation Download Citation

Jianfeng Ren, Nasser Kehtarnavaz, and Madhukar Budagavi "Fast adaptive early termination for mode selection in H.264/AVC standard based on ×264 implementation", Proc. SPIE 6811, Real-Time Image Processing 2008, 68110A (26 February 2008); https://doi.org/10.1117/12.767665

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available