The proposed method analyses local image statistics and then matches the local histograms of two images to be fused by applying mean or mean variance matching normalization functions.
该方法分析了局部影像统计特性，应用均值或均值—方差匹配正态函数，对要融合的两幅影像局部直方图进行匹配。
Then, the best threshold value is calculated basing on the gradient magnitude mean and the variance of the image.
再由图像的梯度幅值均值和方差计算出图像的最佳阈值。
For the regions in image where gray value is high or change intensely, local mean value and variance is adopted to control enhancement coefficients.
针对图像中的高灰度区和灰度剧变区，应用图像局部均值和方差自适应调节增强系数。
For regions with high grey-scale level or with tensely variable grey level, the image enhancement coefficients shall be adaptively controlled based on local mean value and variance.
针对图像中的高灰度区和灰度剧变区，应用图像局部均值和方差自适应调节增强系数。
The images gradient magnitude mean and the variance of every pixel in the image relative to the gradient magnitude mean are calculated according to the method proposed in the paper.
针对传统分水岭变换对图像进行分割时常见的过度分割情况，提出了利用先验知识对梯度幅度图像进行处理的方法。
Based on the mean value and variance, the image normalizing is to reduce the variations of gray between fingerprint ridges and furrows;
个体指纹被采集成指纹图像后，首先采用基于自身灰度均值和方差的规格化方法，降低指纹脊、谷线之间的灰度变化程度；
Based on the mean value and variance, the image normalizing is to reduce the variations of gray between fingerprint ridges and furrows;
个体指纹被采集成指纹图像后，首先采用基于自身灰度均值和方差的规格化方法，降低指纹脊、谷线之间的灰度变化程度；
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