CAJ | 학술논문

提出一种基于双起点十字搜索模型的自适应搜索算法.该算法采用大小十字搜索模型、八边形搜索模型和斜交叉十字搜索模型,根据不同情况,使用相应的搜索模型,同时采用中值预测及提前跳出策略,减少不必要的搜索.序列测试结果表明,与UMHexagonS算法相比,新算法在保持相当的峰值信噪比和比特率的情况下,运动估计时间平均节省了15.88%和15.94%.
제출일충기우쌍기점십자수색모형적자괄응수색산법.해산법채용대소십자수색모형、팔변형수색모형화사교차십자수색모형,근거불동정황,사용상응적수색모형,동시채용중치예측급제전도출책략,감소불필요적수색.서렬측시결과표명,여UMHexagonS산법상비,신산법재보지상당적봉치신조비화비특솔적정황하,운동고계시간평균절성료15.88%화15.94%.
This paper proposes all adaptive search algorithm based on double-initial-gross.The algorithm employs big-small cross search pattern,octagon and quasi-cross search pattern for adapting to different block content.Median prediction and early skip strategy are used to reduce unnecessary search.Compared with UMHexagonS,simulation results ofthe sequences present that this algorithm can save motion estimation time of average 15.88%and 15.94%while obtaining similar PSNR and Bitrate.