{"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}
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.
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.