提出了一种稳健的用于磁共振图像噪声过滤的非抽取小波域方法。这种方法通过一个单一的参数来平衡降噪程度和相关细节的保护。这个算法开发了一种通用的关于不同尺度级间重要图像特征相关性的有效知识来完成预备的系数分类。这种预备系数分类被用来先验估计图像特征和噪声系数的统计学的分布。使用具有局部空间活跃性的小波域标记能达到对图像空间上下文关系的适应。实验结果表明它在磁共振图像抑噪方面的高效性。
In the text, a robust undecimated wavelet domain noise filtering method for magnetic resonance (MR)images was proposed. A single parameter was used to balance the degree of noise reduction and preservation of relevant details. The algorithm developed a generally valid knowledge about significant image features across the wavelet scales to perform a preliminary coefficient classification ,which was used to empirically estimate the statistical distribution of image features or noise coefficients. A wavelet domain indicator of the local spatial activity achieved the adaption to the spatial context in the image. The results show its efficiency in MRI denoising.