摘要
针对传统的单尺度图像增强算法的不足,提出了一种基于Laplace多尺度分解的图像增强算法。该算法将图像分为由高频到低频若干个子图像,对每个频道的细节图像进行不同的非线性变换,使得图像中最细微的、对诊断有用的信息得到有效的增强,同时图像又不被过增强,再通过分解的逆过程重建图像。试验表明,该方法能有效提高图像中细节的清晰度并抑制噪声。
In view of the defects of traditional single scale image enhancement methods,a medical image enhancement method based on multi-scale laplacian decomposition was proposed.The original image was firstly decomposed into certain number of frequency channels from high frequency to low frequency.These detail images were enhanced by different nonlinear transformation to enhance the subtle and diagnosis-important information,and then the multi-scale representation was converted back into the reconstructed image.The experimental results showed that the proposed method could effectively improve image clarity.
出处
《农业网络信息》
2010年第11期142-144,共3页
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