摘要
对于实际的视频编码系统,由CCD摄像机等成像设备所获取的视频信号不可避免地会受到各种类型的噪声的影响。噪声的存在,不仅会对视觉意义上的图像质量产生影响,而且会对后续的编码效率产生负面影响。通过分析CCD噪声的特点以及噪声项对宏块的和范数差值(SND)与绝对差值之和(SAD)所产生的影响,研究了一种应用于噪声视频的两阶段连续消除算法。为了减少用于视频噪声估计的附加计算开销,从统计分析出发,提出了一种利用块匹配计算所得的SAD进行噪声方差估计的方法。实验表明,估计所得的噪声方差的精度,足以满足运动估计算法的需要;而基于噪声方差自适应的连续消除算法能以比连续消除算法少得多的计算代价,获得接近于全搜索的搜索精度。
In a practical video encoder,a video sequence obtained from a CCD camera inevitably conveys noise.The noise term degrades not only image quality but also coding efficiency.By analyzing the characteristics of CCD noise and taking into account the impact of video noise upon Sum Norm Difference（SND） and Sum of Absolute Difference（SAD）of a macro-block,a Noise Variance Adaptive two-stage Successive Elimination Algorithm（NVA-SEA） for block motion estimation is presented.For reducing the additional computation cost,a noise variance estimation scheme that utilizes the by-product of block matching is also proposed.Simulation results demonstrate that the estimated noise variance is accurate enough for the application.The proposed NVASEA can achieve almost the same performance as that of SEA with considerable complexity reduction.
出处
《计算机工程与应用》
CSCD
北大核心
2010年第7期208-212,共5页
Computer Engineering and Applications
关键词
块匹配
连续消除算法
Gaussian噪声
噪声滤波
block matching
Successive Elimination Algorithm（SEA）
Gaussian noise
noise estimation
