Abstract
Motion estimation (ME) and motion compensation (MC) using variable block size, sub-pixel search, and multiple reference frames (MRFs) are the major reasons for improved coding performance of the H.264 video coding standard over other contemporary coding standards. The concept of MRFs is suitable for repetitive motion, uncovered background, non-integer pixel displacement, lighting change, etc. The requirement of index codes of the reference frames, computational time in ME & MC, and memory buffer for coded frames limits the number of reference frames used in practical applications. In typical video sequences, the previous frame is used as a reference frame with 68'92% of cases. In this article, we propose a new video coding method using a reference frame [i.e., the most common frame in scene (McFIS)] generated by dynamic background modeling. McFIS is more effective in terms of rate-distortion and computational time performance compared to the MRFs techniques. It has also inherent capability of scene change detection (SCD) for adaptive group of picture (GOP) size determination. As a result, we integrate SCD (for GOP determination) with reference frame generation. The experimental results show that the proposed coding scheme outperforms the H.264 video coding with five reference frames and the two relevant state-of-the-art algorithms by 0.5'2.0 dB with less computational time.
Original language | English |
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Pages (from-to) | 1-17 |
Number of pages | 17 |
Journal | Eurasip Journal on Advances in Signal Processing |
Volume | 2013 |
Issue number | 11 |
DOIs | |
Publication status | Published - Jan 2013 |
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Integrating knowledge from computer vision, coding and human-computer interaction to achieve ultra-compression of video data
Paul, M. (Creator)
Impact: Economic Impact, Quality of life Impact