无时钟物理计算实现高斯金字塔SIFT算法
Physical Computing With No Clock to Implement the Gaussian Pyramid of SIFT Algorithm
摘要：
物理计算是一种利用电子设备和电路拓扑的性质来处理计算任务的技术。本文提出了一种有源电路网络来实现多尺度高斯滤波器，在图像预处理中也称为高斯金字塔。在图像特征提取算法的关键阶段，人们尝试了各种方法来加速。与现有的GPU并行计算和FPGA加速技术相比，物理计算在处理速度和功耗方面具有很大的优势。通过物理计算技术验证了实现SIFT算法的高斯金字塔的处理时间可以达到纳秒级，而现有的其他方法至少需要数百毫秒。通过对电路杂散电容的估计，滤波256x256图像的功耗约为670pJ。据我们所知，这是最快的处理技术，以加速SIFT算法，它也是一个相当节能的方法，由于所提出的物理计算技术。
英文摘要：
Physical computing is a technology utilizing the nature of electronic devices and circuit topology to cope with computing tasks. In this paper, we propose an active circuit network to implement multi-scale Gaussian filter, which is also called Gaussian Pyramid in image preprocessing. Various kinds of methods have been tried to accelerate the key stage in image feature extracting algorithm these years. Compared with existing technologies, GPU parallel computing and FPGA accelerating technology, physical computing has great advantage on processing speed as well as power consumption. We have verified that processing time to implement the Gaussian pyramid of the SIFT algorithm stands on nanosecond level through the physical computing technology, while other existing methods all need at least hundreds of millisecond. With an estimate on the stray capacitance of the circuit, the power consumption is around 670pJ to filter a 256x256 image. To the best of our knowledge, this is the most fast processing technology to accelerate the SIFT algorithm, and it is also a rather energy-efficient method, thanks to the proposed physical computing technology.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
