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A scalable architecture for implementing the fast discrete periodic radon transform for prime sized images

机译:一种可扩展的体系结构,用于为素尺寸图像实现快速离散的周期性radon变换

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The Discrete Periodic Radon Transform (DPRT) has many important applications in image processing that are associated with reconstructing objects from projections (e.g., computed tomography [1]) or image restoration (e.g., [2]). Thus, there is strong interest in the development of fast algorithms and architectures for computing the DPRT. This paper introduces a scalable hardware architecture and associated algorithm for computing the DPRT for prime-sized images. For square images of size N × N, N prime, the DPRT requires N (N - 1) additions for calculating image projections along a minimal number of prime directions. The proposed approach can compute the DPRT in [N/2] N + 2N + h clock cycles, h = 1, ..., [log N], where h is a scaling factor that is used to control the required hardware resources that are needed to implement the fast DPRT. Compared to previous approaches, a fundamental contribution of the proposed architecture is that it allows effective implementations based on different constraints on the resources.
机译:离散周期Rad变换(DPRT)在图像处理中有许多重要的应用,这些应用与从投影(例如,计算机断层扫描[1])或图像恢复(例如,[2])重建对象有关。因此,人们对开发用于计算DPRT的快速算法和体系结构非常感兴趣。本文介绍了一种可扩展的硬件体系结构和相关算法,用于计算素数图像的DPRT。对于大小为N×N,N个素数的正方形图像,DPRT需要添加N(N-1)个附加值,才能沿着最小数量的素数方向计算图像投影。所提出的方法可以在[N / 2] N + 2N + h个时钟周期(h = 1,...,[log N])中计算DPRT,其中h是用于控制所需硬件资源的比例因子。需要实施快速DPRT。与以前的方法相比,所提出的体系结构的根本贡献在于,它允许基于对资源的不同约束进行有效的实现。

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