引入像素强度的先验概率分布模型，运用模拟退火算法选择合适的邻域结构，获得强度的最优估计。
The prior information of pixel intense distribution is introduced. Then simulated annealing algorithm is applied to choose the proper neighborhood structure, and the optimal estimate can be obtained.
针对模式分类中高置信度的先验概率分布难以设定的问题，提出了一种新的应用贝叶斯分析进行模式分类的方法。
To overcome the hardship of enacting the pre-probability distribution with high certainty factor, this paper proposes one novel way of applying Bayes analysis to classify pattern.
然后，结合图像帧间的差分信息以及灰度分布的先验概率等因素将图像从空间域映射至统计域。
Then, every frame is mapped from spatial domain to statistical domain incorporating the factors such as the difference image from the consecutive frames and the prior distribution of a pixel density.
然后，结合图像帧间的差分信息以及灰度分布的先验概率等因素将图像从空间域映射至统计域。
Then, every frame is mapped from spatial domain to statistical domain incorporating the factors such as the difference image from the consecutive frames and the prior distribution of a pixel density.
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