CAJ | 학술논문

提出一种新的基于运动估计的数据分割方法,在无线网络上传输视频流时能够有效地降低误差扩散.该方法将宏块作为基本的处理对象,根据两个方面将一个编码帧的所有宏块区分为重要性不同的级别:一方面是宏块对本帧图像质量的影响,另一方面是宏块对下一编码帧可能产生的误差扩散的影响.根据宏块中的像素被下一编码帧参考的次数总合来评估误差扩散的影响.在此基础上,码流被分为三种不同级别的子流,分别执行不同速率的信道编码,以保证在满足带宽约束的条件下,重要的信息和宏块数据能被优先保护.除了与其它方法一样能改善视频质量,本文方法的一个明显优势是平衡当前帧的质量与下一帧的质量.实验结果表明,比较263++和h.264中给出的数据分割方法,在两状态马尔可夫信道模型下,本文方法能获得更稳定的和更好的视频质量,提高PSNR值超过0.3dB.
제출일충신적기우운동고계적수거분할방법,재무선망락상전수시빈류시능구유효지강저오차확산.해방법장굉괴작위기본적처리대상,근거량개방면장일개편마정적소유굉괴구분위중요성불동적급별:일방면시굉괴대본정도상질량적영향,령일방면시굉괴대하일편마정가능산생적오차확산적영향.근거굉괴중적상소피하일편마정삼고적차수총합래평고오차확산적영향.재차기출상,마류피분위삼충불동급별적자류,분별집행불동속솔적신도편마,이보증재만족대관약속적조건하,중요적신식화굉괴수거능피우선보호.제료여기타방법일양능개선시빈질량,본문방법적일개명현우세시평형당전정적질량여하일정적질량.실험결과표명,비교263++화h.264중급출적수거분할방법,재량상태마이가부신도모형하,본문방법능획득경은정적화경호적시빈질량,제고PSNR치초과0.3dB.
To prevent error propagation when transmitting video streaming over wireless networks, this paper presents a novel data partitioning method based on motion estimation. Macroblock is treated as basic unit in this method, and all macroblocks within a coded frame are differentiated into different levels of importance according to their own impact factor which is defined based on combination of two types of impact: one is the impact of a macroblock on the quality of next frame and the other is the impact on the quality of current frame. The first impact is evaluated by counting the total of referred times of all pixel within the macroblock and the second one is evaluated by calculating difference between original and predicted macroblock. Then, combined with header information, all macroblocks of a coded frame is partitioned into three types of partitions. Finally, different rates of FEC channel code are applied to different partitions so that the important data can be protected better. While improving the quality of video like other data partitioning methods, an advantage of the proposed method is to balance the quality of the current and the next frame. Compared with other data partitioning methods such as in H.263 + + and H. 264, the proposed method can efficiently limit error and prevent error propagation. Experimental results show the proposed method has obtained stable quality for entire video sequence and achieve better PSNR with the two-state Markov channel model, and the gains are more than 0.3dB.