Research on Edge Detection Optical Computing based on Four Wave Mixing Effect

ZHANG Hongbo; ZHAO Sihao; CAI Ju; ZHANG Min; WAN Feng; WANG Sen; SHANG Debang

doi:10.13756/j.gtxyj.2025.250241

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Research on Edge Detection Optical Computing based on Four Wave Mixing Effect

更新时间：2025-10-15

- Research on Edge Detection Optical Computing based on Four Wave Mixing Effect
- Study on Optical Communications Issue 5, (2025)
- 作者机构：
  
  1.成都信息工程大学　通信工程学院，成都　610225
  2.天府绛溪实验室，成都　641419
- 作者简介：
- 基金信息：
- DOI：10.13756/j.gtxyj.2025.250241
  CLC： O437
- Received：01 July 2025，
  
  Revised：2025-07-21，
  
  Published：10 October 2025
- 稿件说明：
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张洪波，赵思豪，蔡炬，等. 基于四波混频效应的边缘检测光计算研究[J]. 光通信研究，2025(5): 250241.

Zhang H B, Zhao S H, Cai J, et al. Research on Edge Detection Optical Computing based on Four Wave Mixing Effect[J]. Study on Optical Communications, 2025(5): 250241.
张洪波，赵思豪，蔡炬，等. 基于四波混频效应的边缘检测光计算研究[J]. 光通信研究，2025(5): 250241. DOI： 10.13756/j.gtxyj.2025.250241.

Zhang H B, Zhao S H, Cai J, et al. Research on Edge Detection Optical Computing based on Four Wave Mixing Effect[J]. Study on Optical Communications, 2025(5): 250241. DOI： 10.13756/j.gtxyj.2025.250241.

摘要

【目的】

为应对传统边缘检测存在的运算速度瓶颈与高能耗问题，文章提出了一种基于四波混频（FWM）效应的边缘检测光计算方法。

【方法】

该方法利用FWM效应完成边缘检测中梯度计算的乘法运算，随后利用数字信号处理技术完成边缘检测。为验证其处理速度与检测准确性，文章利用FWM效应完成边缘检测并构建了可实现10 Gbit/s高速图像处理的仿真平台，深入研究了载波频偏与卷积核类型对检测性能的影响。

【结果】

结果表明，在系统性能方面，该方法的能耗和时延分别为0.25 pJ/bit和0.98 μs，优于传统计算方案。此外，文章深入研究了载波频偏对边缘检测结果的影响。当承载边缘检测结果的信号与承载卷积核的载波信号中心频率间隔10 GHz时，二者频谱显著重叠，相关性系数仅为0.151 64。当承载卷积核的载波频偏为图像数据载波频偏的两倍时，采用水平或垂直方向卷积核进行边缘检测会受到显著干扰，相关性系数最低降至0.249 9；而在相同条件下，采用全方向卷积核则能够显著提升检测性能，相关性系数最高可达0.947 22。

【结论】

研究表明，该方法能进行高速乘法运算，而且通过合理调整载波频偏和优化卷积核选择，可进一步提升检测精度。

Abstract

【Objective】

To address the bottlenecks of computational speed and high energy consumption in traditional edge detection

this study proposes an optical computing method for edge detection based on the Four Wave Mixing (FWM) effect.

【Methods】

This method uses the FWM effect to complete the multiplication operation of gradient calculation in edge detection

and then uses digital signal processing technology to complete the edge detection. To validate the method's processing speed and detection accuracy

a simulation platform capable of 10 Gbit/s high-speed image processing was established. The influence of carrier frequency offsets and convolution kernel types on detection performance was systematically investigated.

【Results】

The results demonstrate superior system performance

with an energy consumption of 0.25 pJ/bit and a latency of 0.98 μs

outperforming conventional computing schemes. Regarding interference

a 10 GHz frequency separation between the resulting signal and the kernel-carrying carrier led to significant spectral overlap

reducing the correlation coefficient to just 0.151 64. Furthermore

under specific interference conditions where the kernel carrier's frequency offset was twice that of the data carrier

using single-direction (horizontal or vertical) kernels caused severe disruption (correlation coefficient dropping to 0.249 9). In contrast

employing an omnidirectional kernel under the same conditions significantly enhanced the detection performance

achieving a correlation coefficient as high as 0.947 22.

【Conclusion】

This study demonstrates that the proposed method not only enables high-speed multiplication but also achieves higher detection accuracy through the rational configuration of carrier frequency offsets and optimization of convolution kernel selection.

关键词

Keywords

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