ID	原文	译文
25405	以非下采样剪切波变换(NSST)及隐马尔可夫树(HMT)理论为基础，提出了一种基于 BKF(Bessel KForm)矢量 HMT 的非下采样剪切波域图像水印算法。	In this paper, we propose a blind NSST domain image watermark decoder, where in a vector-based HMT statistical model using BKF distribution is used.
25406	水印嵌入时，首先对原始载体图像进行 NSST;然后构造自适应高阶水印嵌入强度函数;最后选择重要的 NSST 高频系数乘性嵌入水印。	In the proposed scheme, the NSST is firstly performed on the original hostimage, and then the adaptive high-order watermark embedding strength functions are constructed, and finally the watermarkdata is embedded into the significant high-frequency coefficients in NSST domain．
25407	水印检测时，首先根据 NSST 系数的非高斯分布特性及 NSST 系数间的子带内、方向间、尺度间等多种相关特性，建立具有强描述能力的 BKF 矢量 HMT 模型;	At the watermark receiver, NSST high pass coefficients are firstly modeled by employing the BKF vector HMT, where the BKF marginal statistics and strong intra-sub-band, cross-scale, and cross-orientation dependencies of NSST coefficients are incorporated.
25408	然后利用最大期望(EM)方法，估计出 BKF 矢量 HMT 模型参数;	Then the statistical model parameters of BKF vector HMT are estimated using the expectation maximization approach．
25409	最后结合 BKF 矢量 HMT 模型和最大似然(ML)检验理论，构造出数字水印检测器并提取水印。	And finally a blind image watermark decoder is developed using BKF vector HMT and the maximum likelihood decision rule．
25410	仿真实验结果证明了本文算法的有效性。	The experimental results validatethe effectiveness of the proposed technique．
25411	本文根据高动态飞行器平台终端的特点，研究了高动态飞行器平台终端通信中的频率精确估计技术，提出了一种频率精确估计分解算法。	According to the characteristics of high dynamic aircraft platform terminal, this paper studies the problem of frequency accurate estimation in high dynamic aircraft platform terminal communication, and proposes a decomposition algorithm for frequency estimation accurately．
25412	首先，基于分段搜索，确定导频帧的大致位置，并估计出频偏的粗略值;	Firstly, the approximate position of pilot frame is determined and approximate value of frequency offset is estimated based on the segmented search．
25413	其次，通过移频搜索法，确定各数据帧的准确位置，以及更高的频偏估计精度，对数据帧解扩;	Secondly, the accurate position of each date frame is determined by the frequency offset search method, and the higher frequency offset estimation accuracy is obtained by which data frame is de-expanded．
25414	最后，利用数据帧中的 PN 字段进一步提高频偏估计精度，并利用频偏方程将各历史数据联立起来构成方程组，得到并跟踪频偏的变化规律。	Finally, the PN field in data frame is used to further improve frequency offset estimation accurately, and frequency offset equation and historical data are combined to form a set of equations, by which the change rule of frequency offset is obtained and tracked．