Evaluating Event-Based Vision Sensing in Rain and Fog

IF 4.3 2区综合性期刊 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Sensors Journal Pub Date : 2025-07-08 DOI:10.1109/JSEN.2025.3584460

Ethan Delaney;Tim Brophy;Enda Ward;Fiachra Collins;Edward Jones;Brian Deegan;Martin Glavin

{"title":"Evaluating Event-Based Vision Sensing in Rain and Fog","authors":"Ethan Delaney;Tim Brophy;Enda Ward;Fiachra Collins;Edward Jones;Brian Deegan;Martin Glavin","doi":"10.1109/JSEN.2025.3584460","DOIUrl":null,"url":null,"abstract":"Event-based vision sensors have a higher temporal resolution, a wider dynamic range, and a lower latency than conventional frame-based cameras. For these reasons, event-based sensors are being considered for advanced driver assistance system (ADAS) applications. If these sensors are to be used for automotive sensing and perception, their performance under adverse conditions, such as rain and fog, must be characterized to ensure reliable performance. This study presents a suite of tests using an event-based sensor under controlled conditions across a range of rainfall rates, ambient light levels, fog visibility levels, and distances from the targets. To evaluate the performance of these sensors, the average event rate (number of events per second) was compared with rainfall rates and visibility. The results indicated that the diameter of the raindrops had a larger effect on the number of events than the rainfall rate. Furthermore, the investigation revealed that, by carefully configuring the camera settings, it is possible to mitigate the effects of rain on the sensor output.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 16","pages":"31545-31562"},"PeriodicalIF":4.3000,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11074301","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Sensors Journal","FirstCategoryId":"103","ListUrlMain":"https://ieeexplore.ieee.org/document/11074301/","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}

引用次数: 0

Abstract

Event-based vision sensors have a higher temporal resolution, a wider dynamic range, and a lower latency than conventional frame-based cameras. For these reasons, event-based sensors are being considered for advanced driver assistance system (ADAS) applications. If these sensors are to be used for automotive sensing and perception, their performance under adverse conditions, such as rain and fog, must be characterized to ensure reliable performance. This study presents a suite of tests using an event-based sensor under controlled conditions across a range of rainfall rates, ambient light levels, fog visibility levels, and distances from the targets. To evaluate the performance of these sensors, the average event rate (number of events per second) was compared with rainfall rates and visibility. The results indicated that the diameter of the raindrops had a larger effect on the number of events than the rainfall rate. Furthermore, the investigation revealed that, by carefully configuring the camera settings, it is possible to mitigate the effects of rain on the sensor output.

查看原文本刊更多论文

雨雾环境下基于事件的视觉感知评价

与传统的基于帧的相机相比，基于事件的视觉传感器具有更高的时间分辨率、更宽的动态范围和更低的延迟。基于这些原因，基于事件的传感器正被考虑用于高级驾驶辅助系统（ADAS）应用。如果这些传感器要用于汽车传感和感知，则必须对其在恶劣条件下（如雨和雾）的性能进行表征，以确保可靠的性能。本研究提出了一套在受控条件下使用基于事件的传感器的测试，包括降雨率、环境光照水平、雾能见度水平和与目标的距离。为了评估这些传感器的性能，将平均事件率（每秒事件数）与降雨量和能见度进行了比较。结果表明，雨滴直径对事件数的影响大于降雨速率。此外，调查显示，通过仔细配置相机设置，可以减轻雨水对传感器输出的影响。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

IEEE Sensors Journal 工程技术-工程：电子与电气

CiteScore

7.70

自引率

14.00%

发文量

2058

审稿时长

5.2 months

期刊介绍： The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following: -Sensor Phenomenology, Modelling, and Evaluation -Sensor Materials, Processing, and Fabrication -Chemical and Gas Sensors -Microfluidics and Biosensors -Optical Sensors -Physical Sensors: Temperature, Mechanical, Magnetic, and others -Acoustic and Ultrasonic Sensors -Sensor Packaging -Sensor Networks -Sensor Applications -Sensor Systems: Signals, Processing, and Interfaces -Actuators and Sensor Power Systems -Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting -Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data) -Sensors in Industrial Practice