邻域小波自适应降噪在X射线图像处理中的应用

Application of Locally Adaptive Wavelet Domain Denosing to X- Ray Image Processing

针对使用低剂量的X射线成像时,会带来泊松噪声和高斯白噪声,影响成像质量。目前对X射线图像的降噪方法主要是针对高斯白噪声模型,而泊松噪声和高斯白噪声是两种不同性质的噪声,因而传统的降噪方法不能有效地去除泊松噪声。邻域小波自适应降噪法,就是在不同的小波高频子代根据最大的噪声方差自适应的调整阈值,然后使用贝叶斯收缩算法,达到同时去除二种噪声的目的。试验证明该方法不仅在去除射线图像噪声时效果显著,同时还能更好地保留图像中的边缘细节。

When imaging in low - dose X - Ray, some noise which obeys the Possion Distribution or the Gauss Distribution will appear , which does harm to the image quality. Now the denosing method for images is mainly based on the Gauss White Noise model, so it is not efficacious to remove the Possion noise in traditional means as the different nature between Possion noise and Gauss White noise. The locally adaptive wavelet domain denosing method which adaptivly adjusts the threhold based on the maximum noise variance in various detail wavelet subbands will be given. Experinmetal results show that the proposed method always outperforms the traditional ways in noise removal and the edge details reservation for degraded images.