样条草图:光子计数激光雷达的高效方法

IF 4.2 2区 计算机科学 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Michael P. Sheehan;Julián Tachella;Mike E. Davies
{"title":"样条草图:光子计数激光雷达的高效方法","authors":"Michael P. Sheehan;Julián Tachella;Mike E. Davies","doi":"10.1109/TCI.2024.3404652","DOIUrl":null,"url":null,"abstract":"Photon counting lidar has become an invaluable tool for 3D depth imaging due to the fine depth precision it can achieve over long ranges, with emerging applications in robotics, autonomous vehicles and remote sensing. However, high frame rate, high resolution lidar devices produce an enormous amount of time-of-flight (ToF) data which can cause a severe data processing bottleneck hindering the deployment of real-time systems. In this paper, we show that this bottleneck can be avoided through the use of a hardware-friendly compressed statistic, or a so-called spline sketch, of the ToF data, massively reducing the data rate without sacrificing the quality of the recovered depth image. Specifically, as with the previously proposed Fourier sketches, piecewise linear or quadratic spline sketches are able to reconstruct real-world depth images with negligible loss of resolution whilst achieving 95% compression compared to the full ToF data, as well as offering multi-peak detection performance. However, unlike Fourier sketches, splines sketches require minimal on-chip arithmetic computation per photon detection. We also show that by building in appropriate range-walk correction, spline sketches can be made robust to photon pile-up effects associated with bright reflectors. We contrast this with previously proposed solutions such as coarse binning histograms that trade depth resolution for data compression, suffer from a highly nonuniform accuracy across depth and can fail catastrophically when imaging bright reflectors. By providing a practical means of overcoming the data processing bottleneck, spline sketches offer a promising route to low cost high rate, high resolution lidar imaging.","PeriodicalId":56022,"journal":{"name":"IEEE Transactions on Computational Imaging","volume":"10 ","pages":"863-875"},"PeriodicalIF":4.2000,"publicationDate":"2024-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Spline Sketches: An Efficient Approach for Photon Counting Lidar\",\"authors\":\"Michael P. Sheehan;Julián Tachella;Mike E. Davies\",\"doi\":\"10.1109/TCI.2024.3404652\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Photon counting lidar has become an invaluable tool for 3D depth imaging due to the fine depth precision it can achieve over long ranges, with emerging applications in robotics, autonomous vehicles and remote sensing. However, high frame rate, high resolution lidar devices produce an enormous amount of time-of-flight (ToF) data which can cause a severe data processing bottleneck hindering the deployment of real-time systems. In this paper, we show that this bottleneck can be avoided through the use of a hardware-friendly compressed statistic, or a so-called spline sketch, of the ToF data, massively reducing the data rate without sacrificing the quality of the recovered depth image. Specifically, as with the previously proposed Fourier sketches, piecewise linear or quadratic spline sketches are able to reconstruct real-world depth images with negligible loss of resolution whilst achieving 95% compression compared to the full ToF data, as well as offering multi-peak detection performance. However, unlike Fourier sketches, splines sketches require minimal on-chip arithmetic computation per photon detection. We also show that by building in appropriate range-walk correction, spline sketches can be made robust to photon pile-up effects associated with bright reflectors. We contrast this with previously proposed solutions such as coarse binning histograms that trade depth resolution for data compression, suffer from a highly nonuniform accuracy across depth and can fail catastrophically when imaging bright reflectors. By providing a practical means of overcoming the data processing bottleneck, spline sketches offer a promising route to low cost high rate, high resolution lidar imaging.\",\"PeriodicalId\":56022,\"journal\":{\"name\":\"IEEE Transactions on Computational Imaging\",\"volume\":\"10 \",\"pages\":\"863-875\"},\"PeriodicalIF\":4.2000,\"publicationDate\":\"2024-03-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Computational Imaging\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10538007/\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Computational Imaging","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10538007/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0

摘要

光子计数激光雷达可在远距离上实现精细的深度精度,因此已成为三维深度成像的宝贵工具,并在机器人、自动驾驶汽车和遥感领域得到新兴应用。然而,高帧率、高分辨率激光雷达设备会产生大量的飞行时间(ToF)数据,这会造成严重的数据处理瓶颈,阻碍实时系统的部署。在本文中,我们展示了通过对 ToF 数据使用硬件友好的压缩统计量(即所谓的样条草图)来避免这一瓶颈,从而在不牺牲恢复深度图像质量的情况下大幅降低数据速率。具体来说,与之前提出的傅立叶草图一样,片断线性或二次样条草图能够以可忽略不计的分辨率损失重建真实世界的深度图像,与完整的 ToF 数据相比,压缩率达到 95%,并具有多峰值检测性能。然而,与傅立叶草图不同的是,每检测一个光子,样条草图需要的片上算术计算量极少。我们还表明,通过内置适当的测距误差校正,样条草图可以抵御与明亮反射器相关的光子堆积效应。我们将其与之前提出的解决方案(如粗分档直方图)进行对比,粗分档直方图以深度分辨率换取数据压缩,在深度上精度极不均匀,在对明亮反射体成像时可能会出现灾难性的失败。通过提供克服数据处理瓶颈的实用方法,样条草图为低成本、高速率、高分辨率激光雷达成像提供了一条前景广阔的途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spline Sketches: An Efficient Approach for Photon Counting Lidar
Photon counting lidar has become an invaluable tool for 3D depth imaging due to the fine depth precision it can achieve over long ranges, with emerging applications in robotics, autonomous vehicles and remote sensing. However, high frame rate, high resolution lidar devices produce an enormous amount of time-of-flight (ToF) data which can cause a severe data processing bottleneck hindering the deployment of real-time systems. In this paper, we show that this bottleneck can be avoided through the use of a hardware-friendly compressed statistic, or a so-called spline sketch, of the ToF data, massively reducing the data rate without sacrificing the quality of the recovered depth image. Specifically, as with the previously proposed Fourier sketches, piecewise linear or quadratic spline sketches are able to reconstruct real-world depth images with negligible loss of resolution whilst achieving 95% compression compared to the full ToF data, as well as offering multi-peak detection performance. However, unlike Fourier sketches, splines sketches require minimal on-chip arithmetic computation per photon detection. We also show that by building in appropriate range-walk correction, spline sketches can be made robust to photon pile-up effects associated with bright reflectors. We contrast this with previously proposed solutions such as coarse binning histograms that trade depth resolution for data compression, suffer from a highly nonuniform accuracy across depth and can fail catastrophically when imaging bright reflectors. By providing a practical means of overcoming the data processing bottleneck, spline sketches offer a promising route to low cost high rate, high resolution lidar imaging.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
IEEE Transactions on Computational Imaging
IEEE Transactions on Computational Imaging Mathematics-Computational Mathematics
CiteScore
8.20
自引率
7.40%
发文量
59
期刊介绍: The IEEE Transactions on Computational Imaging will publish articles where computation plays an integral role in the image formation process. Papers will cover all areas of computational imaging ranging from fundamental theoretical methods to the latest innovative computational imaging system designs. Topics of interest will include advanced algorithms and mathematical techniques, model-based data inversion, methods for image and signal recovery from sparse and incomplete data, techniques for non-traditional sensing of image data, methods for dynamic information acquisition and extraction from imaging sensors, software and hardware for efficient computation in imaging systems, and highly novel imaging system design.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信