中文摘要：

提出了基于窗口经验模式分解（WEMD）的医学图像增强算法。用WEMD算法分解医学图像,能够自适应地提取图像的内涵模式函数（IMF）分量。利用IMF分量图像的直方图服从正态分布的特性,结合直方图匹配算法的增强能力处理前几个IMF分量,经处理的IMF分量中的高频细节信息得到增强。将处理后的IMF分量和剩余分量重构,获取增强的医学图像。实验表明,WEMD算法增强效果优于目前的图像增强算法。

英文摘要：

A medical image enhancement algorithm based on window empirical mode decomposition（WEMD） is proposed.The high frequency data（intrinsic mode function,IMF） of the medical image can be acquired auto-adaptively by WEMD algorithm.On the basis of the IMF′s histogram following the normal distribution,the high frequency details of the first few IMF components will be enhanced by modifying the IMF components with a histogram matching algorithm.The enhanced image can be obtained by adding up the modified IMF components and the residual component.The results show that the proposed algorithm is efficient in image enhancement and better than other current algorithms.