A Reconfigurable Architecture for Image Processing and Computer Vision
A Reconfigurable Architecture for Image Processing and Computer Vision
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DOI：
10.1142/s0218001495000110
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发表时间：
1995-04
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影响因子：
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通讯作者：
S. Bhandarkar;H. Arabnia;Jeffrey W. Smith
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作者：
S. Bhandarkar;H. Arabnia;Jeffrey W. Smith
在本文中，我们描述了一个可重构的架构，图像处理和计算机视觉的基础上的多环网络，我们称之为可重构多环系统（RMRS）。我们描述了重新配置开关的RMRS，也描述了其VLSI实现。的RMRS拓扑结构被证明是定期和可扩展的，因此非常适合VLSI实现。我们证明了RMRS拓扑结构的一些重要性质，并表明，广泛的一类算法的n-立方体可以映射到RMRS在一个简单而优雅的方式。我们设计和分析了一类程序原语的SIMD RMRS，并展示了如何这些原语可以用来作为构建块更复杂的并行操作。我们证明了有用的RMRS的图像处理和计算机视觉中的问题，通过考虑两个重要的操作-快速傅立叶变换（FFT）和Hough变换检测图像中的线性特征。利用上述程序原语设计了SIMD RMRS上FFT和Hough变换的并行算法。这些算法的复杂性的分析表明，SIMD RMRS是一个可行的架构，在计算机视觉和图像处理的问题。
In this paper we describe a reconfigurable architecture for image processing and computer vision based on a multi-ring network which we call a Reconfigurable Multi-Ring System (RMRS). We describe the reconfiguration switch for the RMRS and also describe its VLSI implementation. The RMRS topology is shown to be regular and scalable and hence well-suited for VLSI implementation. We prove some important properties of the RMRS topology and show that a broad class of algorithms for the n-cube can be mapped to the RMRS in a simple and elegant manner. We design and analyze a class of procedural primitives for the SIMD RMRS and show how these primitives can be used as building blocks for more complex parallel operations. We demonstrate the usefulness of the RMRS for problems in image processing and computer vision by considering two important operations—the Fast Fourier Transform (FFT) and the Hough transform for detection of linear features in an image. Parallel algorithms for the FFT and the Hough transform on the SIMD RMRS are designed using the aforementioned procedural primitives. The analysis of the complexity of these algorithms shows that the SIMD RMRS is a viable architecture for problems in computer vision and image processing.