提出了一种基于小波变换域的块匹配运动估计搜索的新算法，模拟实验表明，利用此算法可获得比一般运动块匹配方法更大的峰值信噪比，具有更好的性能复杂度比。
The authors present a new algorithm for block-matching motion estimation based on wavelet transform. The simulation shows that this algorithm has better PSNR and performance-to-complexity ratio.
此外，利用熵、图像均值、均方根误差、峰值信噪比等参量对该融合方法的融合性能进行评价与分析。
In addition, with the use of the parameters such as entropy, average of image, root mean square error, peak signal-to-noise ratio, the performance of the fusion scheme is evaluated and analyzed.
通过实验验证了该算法的有效性，并以峰值信噪比(PSNR)为评价准则，利用多项式拟合方法选择了最优参数。
Experiments proved the validity of the model. Taking Peak Signal-to-Noise Ratio (PSNR) as criterion the best preference was found by using polynomial fitting.
大量的模拟实验结果表明，利用该算法隐藏的图像在视觉效果和峰值信噪比(PSNR)两方面均优于同类算法。
Experimental results show that both the visual quality and PSNR of the image processed using the proposed error concealment method are better than other temporal algorithms.
大量的模拟实验结果表明，利用该算法隐藏的图像在视觉效果和峰值信噪比(PSNR)两方面均优于同类算法。
Experimental results show that both the visual quality and PSNR of the image processed using the proposed error concealment method are better than other temporal algorithms.
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