基于邻域相关信息的X射线图像增强算法

射线图像存在对比度差、灰度范围小、影像模糊等缺陷。传统的反锐化增强算法是图像增强经常用到的方法，该方法简单易行，但对噪声非常敏感。一般是加上一个低通滤波器来抑制噪声，但加上低通滤波器后又会对边缘造成模糊。 针对上述问题，提出了基于邻域相关信息的射线图像增强算法。首先对射线图像进行多幅叠加降噪，然后根据掩模中心像素和周围邻域像素灰度值的差与输出灰度的查找表进行图像增强。该方法在增强图像的同时能够很好地抑制噪声的增加，实验证明这种方法是可行的。

Enhancement algorithm for X-ray images based on neighborhood related information

There are many defects in X-ray images,such as bad contrast,narrow grayscale range,and fuzzy image.Unsharp masking method is a popular approach for image enhancement,in which a highpass version of an image is added to the original one.This method is easy to run,but is very sensitive to noise.Suppressing noise is generally performed with lowpass filters,and leads to edge blurring.For this problem,a sharpening algorithm for X-ray images based on neighborhood related information is proposed.First,the noise of X-ray images is suppressed by image averaging;then,a lookup table set by the gray difference of pixel at the center of the mask and the neighborhood pixel is used to enhance X-ray images.Enhancing images with the new method can well reduce the addition of noise at the same time.The experimental results have proved the effectiveness of this method.