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An Asynchronous Cellular Logic Network for Trigger-Wave Image Processing on Fine-Grain Massively Parallel Arrays

机译:细粒大规模并行阵列上触发波图像处理的异步蜂窝逻辑网络

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摘要

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-μm 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.
机译:大规模并行每像素处理器单指令多数据阵列已成功用于智能传感器系统中的早期视觉应用。但是,当执行涉及二进制信号传播的算法(例如测地线重建)时,它们固有地效率低下。然而,这些算法应在像素级和对象级图像处理之间的接口上实现,并应在视觉芯片上实现,以促进传感器级数据的减少。本文提出了一种蜂窝异步网络,该网络可用于执行二进制传播操作。所提出的电路在速度和功耗方面进行了优化。在0.35-μm技术中,模拟的传播速度为每个像素0.18 ns,每次传播所消耗的总能量为每个单元0.37 pJ。在本摘要中,讨论了实现问题,并给出了包括图像处理示例的仿真结果。

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