Multidimensional Image Processing via Fast Feature-Preserving Filters

多维图像已成为自然科学和工业工程中观测或测量数据的常用图像。在本研究中，我们开发了一种用于多维图像的特征保持滤波器的快速近似算法。该算法的应用包括图像的降噪、频率分解、区域分割和特征提取。我们的算法在3.2 GHz的PC上滤波5133个体素的图像只需要3分钟，而如此庞大的数据需要大约30年的时间来精确滤波。

Multidimensional images had become popular in natural science and industrial engineering for observed or measured data. In this research, we have developed a fast approximation algorithm of fea-ture-preserving filters for multidimensional images. Application of the developed algorithm includes noise reduction, frequency decomposition, region segmentation, and feature extraction of the images. Filtering the image consisting of 5133 voxels took only 3 minutes by our algorithm with 3.2 GHz PC where the exact filtering requires approximately 30 years for such huge data.