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Fast Reconstruction of 3D Images Using Charlier Discrete Orthogonal Moments

机译:使用Charlier离散正交矩快速重建3D图像

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We propose a new algorithm for accelerating the computation time of Charlier discrete orthogonal moments for three-dimensional (3D) images, based on two fundamental notions: The first is a new representation of 3D images called image cuboid representation (ICR) in which the 3D image is decomposed into a set of cuboids of the same gray level instead of voxels, enabling a considerable reduction in both the amount of treated voxels and the computation time of Charlier moments. The second is a matrix calculation of the Charlier moments instead of direct or recursive calculations. The significant reduction in the computation time for Charlier moments, in combination with the ICR method, motivated the development of this new method for 3D image reconstruction. Simulation results confirm the effectiveness of the proposed method in terms of the calculation time of 3D Charlier moments as well as the speed and quality of image reconstruction.
机译:我们基于两个基本概念,提出了一种用于加快三维(3D)图像的Charlier离散正交矩的计算时间的新算法:第一种是称为图像长方体表示(ICR)的3D图像的新表示,其中3D图像被分解为一组具有相同灰度级的长方体,而不是体素,从而可以大大减少已处理体素的数量和Charlier矩的计算时间。第二个是Charlier矩的矩阵计算,而不是直接或递归计算。与ICR方法相结合,显着减少了Charlier矩的计算时间,从而推动了这种用于3D图像重建的新方法的发展。仿真结果从3D Charlier矩的计算时间以及图像重建的速度和质量方面证实了该方法的有效性。

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