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应用于实时图像匹配的互相关可重构计算电路

A Configurable Circuit for Cross-Correlation in Real-Time Image Matching

  • 摘要: 互相关是基于相关的图像匹配中计算耗时最长的部分。因此如何快速计算互相关是实现实时图像匹配的关键。本文揭示了互相关计算中,现在广泛采用的级联乘累加和并发自累加电路不一定总能带来较好的实时性能。为了获得更好地实时性能和更高的资源利用效率,本文提出了一种兼容级联乘累加和并发自累加各自优点的可重构计算电路,用于全搜索图像匹配中互相关的大量乘累加计算。这种电路根据待匹配图像的尺寸实现电路的重构配置,功能上包含了级联乘累加和并发自累加两种结构,但是采用了可重构设计,并没有带来明显的硬件资源开销增长。计算过程中根据所给出的图像尺寸择优选择一种配置模式完成计算,以获得更好的实时性能和资源利用效率。所提出的电路采用阵列方式工作,并且能够很好的适应图像尺寸变化时的实时匹配处理。实验结果表明这种兼容了两种架构的全新电路能够快速完成大量乘累加的计算,使电路始终工作在高效状态,进一步提高了计算的密集度,并且使用更加灵活方便。

     

    Abstract: Cross-correlation (CC) is the most time-consuming in the implementation of image matching algorithms based on the correlation method. Therefore, how to calculate CC fast is crucial to real-time image matching. This work reveals that the single cascading multiply-accumulate (CAMAC) and concurrent multiply-accumulate (COMAC) architectures which have been widely used in the past, actually, do not necessarily bring about a satisfactory time performance for CC. To obtain better time performance and higher resource efficiency, this paper proposes a configurable circuit involving the advantages of CAMAC and COMAC for a large amount of multiply-accumulate (MAC) operations of CC in exhaustive search. The proposed circuit works in an array manner and can better adapt to changing size image matching in real-time processing. Experimental results demonstrate that this novel circuit which involves the two structures can complete vast MAC calculations at a very high speed. Compared with existing related work, it improves the computation density further and is more flexible to use.

     

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