医学图像融合的效果评价方法有很多，如信息熵、互信息、均方值、峰值信噪比和平均梯度等。
There are many kinds of image fusion methods, such as information entropy, mutual information, mean square error, peak signal to noise ratio and mean grads.
在经典自适应波束形成算法中，常采用均方误差准则，但对于一个通信系统来说，误码率是评价其性能的一个很重要的参数。
Mean square error approach is often adopted in classical adaptive beam-forming algorithm, nevertheless, the bit error rate is one of the most important parameters in a communication system.
通过仿真实验结果及均方误差(MSE)和峰值信噪比(PSNR)两种评价准则说明了该算法的有效性和可行性。
The validity and feasibility of the algorithm is tested through a simulation experiment and two appraisal criterions-mean square error (MSE) and peak value signal to noise ratio (PSNR).
介绍了图像融合的各种评价方法，包括：熵、交叉熵、交互信息量、均方误差、均方根误差、峰值信噪比。
The methods of the evaluation of image fusion, which includes: entropy, cross entropy, mutual information, mean square error, root mean square error, peak-to-peak signal-to-noise ratio were presented.
介绍了图像融合的各种评价方法，包括：熵、交叉熵、交互信息量、均方误差、均方根误差、峰值信噪比。
The methods of the evaluation of image fusion, which includes: entropy, cross entropy, mutual information, mean square error, root mean square error, peak-to-peak signal-to-noise ratio were presented.
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