[1]尹毅,吕培,李凯江,等.基于多尺度动态滤波的图像增强模型[J].郑州大学学报(工学版),2026,47(XX):1-8.[doi:10. 13705 / j. issn. 1671-6833. 2025. 03. 016]
　YIN Yi,LYU Pei,LI Kaijiang,et al.Image Enhancement Model Based on Multi-scale Dynamic Filtering[J].Journal of Zhengzhou University (Engineering Science),2026,47(XX):1-8.[doi:10. 13705 / j. issn. 1671-6833. 2025. 03. 016]
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基于多尺度动态滤波的图像增强模型()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
47
期数:
2026年XX
页码:
1-8
栏目:
出版日期:
2026-09-10

文章信息/Info

Title:
Image Enhancement Model Based on Multi-scale Dynamic Filtering
作者:
尹毅;  吕培;  李凯江;  郑昊坤;  徐豪;  陈梦婕
郑州大学 计算机与人工智能学院，河南 郑州 450001
Author(s):
YIN Yi;  LYU Pei;  LI Kaijiang;  ZHENG Haokun;  XU Hao;  CHEN Mengjie
School of Computer and Artificial Intelligence, Zhengzhou University, Zhengzhou 450001, China
关键词:
图像增强;  低通滤波;  高通滤波;  多尺度融合;  频域变换
Keywords:
image enhancement;  high-pass filtering;  low-pass filtering;  multi-scale fusion;  frequency domain transformation
分类号:
TP37TP391. 9
DOI:
10. 13705 / j. issn. 1671-6833. 2025. 03. 016
文献标志码:
A
摘要:
为提高主动避撞策略的有效性，提出了一种碰撞时间裕度风险评估方法。建立三自由度车辆模型和Dugoff轮胎模型并对状态参数进行计算得到归一化轮胎力。基于无迹卡尔曼滤波算法设计路面附着系数估计器，并通过仿真验证附着系数估计器的有效性。在安全距离模型中加入了道路附着系数，以解决传统避撞模型只考虑位置和车辆运动状况的问题。使用五次多项式生成主动避撞路径，计算所需的安全转向距离。基于风险评估方法设计避撞模式选择策略，使智能车辆可根据与障碍物之间的运动学关系选择合适的避撞模式。采用基于车辆逆动力学模型的纵向控制与使用MPC的横向控制对智能车辆进行解耦控制。通过Carsim-Simulink联合仿真实验和实车试验验证了避撞策略的有效性。
Abstract:
To improve the effectiveness of the active collision avoidance strategy, a risk assessment method for collision time margin is proposed. The three-degree-of-freedom vehicle model and the Dugoff tire model were established, and the state parameters were calculated to obtain the normalized tire force. The pavement adhesion coefficient estimator is designed based on the traceless Kalman filtering algorithm, and the effectiveness of the adhesion coefficient estimator is verified through simulation. The road adhesion coefficient was added to the safety distance model to address the limitations of the traditional collision avoidance model, which only considers the position and the vehicle movement conditions. Generate the active collision avoidance path using a fivetic polynomial and calculate the required safe steering distance. Based on the risk assessment method, a collision avoidance mode selection strategy was designed, enabling intelligent vehicles to select the appropriate collision avoidance mode according to the kinematic relationship with obstacles. The longitudinal control based on the vehicle inverse dynamic model and the lateral control using MPC are adopted to decouple the control of intelligent vehicles. The effectiveness of the collision avoidance strategy was verified through the joint simulation experiment of Carsim and Simulink and the real vehicle test.

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备注/Memo

备注/Memo:
收稿日期:2025-09-07;修订日期:2025-10-21
基金项目:国家自然科学基金面上项目(62372415) ;装备预研教育部联合基金(8091B032257) ;河南省杰出青年科学基金项目(242300421050)
通信作者:吕培(1986— )男,河南孟州人,郑州大学副教授,博士,博士生导师,主要从事人工智能、虚拟现实、外骨骼机器人研究，E-mail:ielvpei@zzu.edu.cn。
更新日期/Last Update: 2026-01-14