Transform model estimation (TME) is a geometric operation, widely utilized in real-time imaging systems. Considering the massive computational load of matrix algebra-based TME realizations, most of the imaging systems resort to highly paralleled software-platform-based TME execution, which is power-intensive and expensive. Due to low-speed and power intensiveness, existing hardware for TME is not capable enough to meet the requirements of real-time systems. In this article, a hardware-realizable method of three-degree-of-freedom TME is formulated encompassing both the conventional CORDIC and the proposed modified CORDIC. The novelties of the proposed TME method and the corresponding architecture are that its latency sublinearly varies with the precision and the total computation time (CT) is almost independent of the input image sizes. The performance of prototype 16-bit fixed-point TME architecture (realized using VHDL in Xilinx Vivado 18.2) is compared with the software-counterpart. The proposed TME hardware is utilized along with other standard hardware modules to realize image registration (IR) operation. The proposed IR architecture achieves, on average, 60% reduction in total CT, 1.61× increase in maximum operating frequency with a comparable accuracy, only at the cost of 23% increase in power consumption with respect to other existing IR hardware.

中文翻译：

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基于 CORDIC 的实时成像变换模型估计高速 VLSI 架构


变换模型估计（TME）是一种几何运算，广泛应用于实时成像系统中。考虑到基于矩阵代数的 TME 实现的巨大计算量，大多数成像系统都采用高度并行的基于软件平台的 TME 执行，这种方法既耗电又昂贵。由于速度低、功耗大，现有的TME硬件不足以满足实时系统的要求。在本文中，制定了一种三自由度 TME 的硬件可实现方法，其中包括传统的 CORDIC 和所提出的改进的 CORDIC。所提出的 TME 方法和相应架构的新颖之处在于，其延迟随精度呈亚线性变化，并且总计算时间 (CT) 几乎与输入图像大小无关。将原型 16 位定点 TME 架构（使用 Xilinx Vivado 18.2 中的 VHDL 实现）的性能与软件对应物进行了比较。所提出的 TME 硬件与其他标准硬件模块一起使用来实现图像配准（IR）操作。与其他现有 IR 硬件相比，所提出的 IR 架构平均可实现总 CT 降低 60%，最大工作频率提高 1.61 倍，且精度相当，而功耗仅增加 23%。