An asynchronous cellular logic network for trigger-wave image processing on fine-grain massively parallel arrays
An asynchronous cellular logic network for trigger-wave image processing on fine-grain massively parallel arrays
复制标题
DOI：
10.1109/tcsii.2006.869916
复制
发表时间：
2006-05-01
影响因子：
4.4
通讯作者：
Dudek, Piotr
中科院分区：
文献类型：
--
作者：
Dudek, Piotr
大规模并行处理器逐像素单指令多数据阵列已成功用于智能传感器系统的早期视觉应用；然而，当执行涉及二进制信号传播的算法时，它们固有地效率低下，例如测地线重建。然而，这些算法在像素级和对象级图像处理的接口上，应该在视觉芯片上实现，以促进传感器级的数据缩减。本文提出了一种可用于二进制传播操作的蜂窝异步网络。所提出的电路在速度和功耗方面进行了优化。在0.35 μ m技术中，模拟传播速度为每像素0.18 ns，每次传播的总能量消耗为每细胞0.37 pJ。本文讨论了实现问题，并给出了包括图像处理实例在内的仿真结果。
Massively parallel processor-per-pixel single-instruction multiple data arrays are being successfully used for early vision applications in smart sensor systems; however, they are inherently inefficient when executing algorithms involving propagation of binary signals, such as the geodesic reconstruction. Yet, these algorithms, at the interface between pixel-level and object-level image processing, should be implemented on the vision chip to facilitate data reduction at the sensor level. A cellular asynchronous network is presented in this paper, which can be used to execute binary propagation operations. The proposed circuit is optimized in terms of speed and power consumption. In 0.35-mu m technology, the simulated propagation speed is 0.18 ns per pixel and the total energy expended per propagation is 0.37 pJ per cell. In this brief, implementation issues are discussed and simulation results including image processing examples are presented.