一种医学图像中细节特征的增强算法

医用X光图像中常伴有对比度偏低和噪声较大等缺点,这些对图像中的细节特征造成很大影响,而这些细节特征在医学图像中通常极为重要.普通的图像增强算法在消除噪声和增强细节特征之间难以做到很好的权衡.利用小波的多分辨率特性和小波分解系数在图像边缘方面的保持特性,对小波分解系数进行双边滤波,从而达到抑制噪声、增强图像的目的.实验表明,该方法能够在保持低失真率的前提下达到较好的增强图像细节特征的效果.同时,该算法可以以迭代的方式使用,从而达到逐步增强的目的.

Enhancement of Detail Characters within Medical Image

Low-contrast and heavy noise are main shortages of X-ray medical images, which makes the images vague and uncertainly. As result,some very useful details characteristic are weakened which are difficult to distinguish even by naked eyes. Based on the analysis of multi-resolution wavelet transform and bilateral filtering operator,a kind of image enhancement algorithm for detail characters was presented. hhe algorithm can enhance the detail characters while confining noise amplifying and keeping lower distortion. The analysis of the results shows that local regions of the image are enhanced by using the 8-neighbor grad contrast of the wavelet transform coefficient, which makes the detail characters of image clearer adaptively. Experiments were conducted on real pictures, and the results show that the algorithm is flexible and convenient.