DOI: 10.1007/978-3-642-15696-0_14 Conference: Advances in Multimedia Information Processing - PCM 2010 - 11th Pacific Rim Conference on Multimedia, Shanghai, China, September 2010, Proceedings, Part II
In this paper, a new fast mode decision (FMD) algorithm is proposed for the state-of-the-art video coding standard H.264/AVC.
Firstly, based on Rate-Distortion (RD) cost characteristics, all inter modes are classified into two groups, one is Skip mode
(including both Skip and Direct modes) and all the other inter modes are called non-Skip modes. In order to select the best
mode for coding a Macroblock (MB), minimum RD costs of these two mode groups are predicted respectively. Then for Skip mode,
an early Skip mode detection scheme is proposed; for non-Skip modes, a three-stage scheme is developed to speed up the mode
decision process. Experimental results demonstrate that the proposed algorithm has good robustness in coding efficiency with
different Quantization parameters (Qps) and various video sequences and is able to achieve about 54% time saving on average
while with negligible degradation in Peak-Signal-to-Noise-Ratio (PSNR) and acceptable increase in bit rate.
"The complexity in determining the prime mode in H.264/ AVC is proposed , which saves encoding time. The proposed method involves Lagrangian optimization with rate and distortion cost to decide the prime mode while achieving less encoding time and coding efficiency. "
[Show abstract][Hide abstract] ABSTRACT: Abstract
H.264 Advanced Video Coding (AVC) was prolonged to Scalable Video Coding (SVC). SVC executes in different electronics gadgets such as personal computer, HDTV, SDTV, IPTV, and full-HDTV in which user demands various scaling of the same content. The various scaling is resolution, frame rate, quality, heterogeneous networks, bandwidth, and so forth. Scaling consumes more encoding time and computational complexity during mode selection. In this paper, to reduce encoding time and computational complexity, a fast mode decision algorithm based on likelihood mode decision (LMD) is proposed. LMD is evaluated in both temporal and spatial scaling. From the results, we conclude that LMD performs well, when compared to the previous fast mode decision algorithms. The comparison parameters are time, PSNR, and bit rate. LMD achieve time saving of 66.65% with 0.05% detriment in PSNR and 0.17% increment in bit rate compared with the full search method.
The Scientific World Journal 06/2015; 2015(418437):10. DOI:10.1155/2015/418437 · 1.73 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The motion estimation and disparity estimation are used to remove the temporal and inter-view redundancies in multiview plus depth video coding, however, the variable block-size ME and DE make the computational complexity increase dramatically. This drawback limits it to be applied in real-time applications. In this paper, based on the mode correlations between depth video and its corresponding texture video, motion prediction and coded block pattern, we propose a fast mode decision algorithm to reduce the computational complexity of multiview depth video coding. Experimental results show that the proposed algorithm can achieve 67.18 and 69.90 % encoding time saving for even and odd views, respectively, while maintaining a comparable rate-distortion performance. In addition, with the dramatic encoding time reduction, the proposed algorithm becomes more suitable for real-time applications.
[Show abstract][Hide abstract] ABSTRACT: H.264/AVC extension is H.264/SVC which is applicable for environment that demands video streaming. This paper presents an algorithm to reduce computation complexity and maintain coding efficiency by determining the mode quickly. Our algorithm terminates mode search by a probability model for both intra-mode and inter-mode of lower level and higher level layers in a Macro Block (MB). The estimated of Rate Distortion Cost (RDC) for modes among layers is used to determine best mode of each MB. This algorithm achieves about 26.9% of the encoding time when compared with JSVM reference software with minimal degradation in PSNR.
Proceedings of the 3rd International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA) 2014, Bhubaneshwar, Odisha; 11/2014
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