{"id":6307,"date":"2023-07-17T07:00:51","date_gmt":"2023-07-17T07:00:51","guid":{"rendered":"https:\/\/cdn.neuvition.com\/?p=6307"},"modified":"2023-07-17T07:00:53","modified_gmt":"2023-07-17T07:00:53","slug":"compression-algorithms","status":"publish","type":"post","link":"https:\/\/www.neuvition.com/zh-CN\/technology-blog\/compression-algorithms.html","title":{"rendered":"压缩算法"},"content":{"rendered":"

压缩算法：这些算法压缩点云数据以减少存储或传输带宽。<\/p>\n\n\n\n

LiDAR点云压缩算法的应用<\/strong><\/p>\n\n\n\n

LiDAR 点云压缩算法用于减小 LiDAR 数据的大小，而不会显著影响其质量或准确性。这一点很重要，因为 LiDAR 数据可能非常大，存储和传输数据可能非常耗时且成本高昂。压缩算法可用于减少 LiDAR 数据的存储和传输要求，同时保留其有用信息。这在需要通过互联网传输 LiDAR 数据或存储在存储容量有限的便携式设备上的应用中特别有用。此外，LiDAR 数据压缩还可以降低处理大型数据集的计算成本，从而更快地分析和可视化数据。总体而言，LiDAR 点云压缩算法在测量、林业、采矿和运输等行业中具有广泛的实际应用。<\/p>\n\n\n\n

以下是 LiDAR 点云压缩算法的十大库：<\/strong><\/p>\n\n\n\n

1.LASzip：https:\/\/laszip.org\/<\/p>\n\n\n\n

LASzip 是一个免费的开源库，用于压缩 LAS 格式的 LiDAR 数据。它提供无损和有损压缩选项，在 LiDAR 社区中被广泛使用。<\/p>\n\n\n\n

2.缠绕：https:\/\/entwine.io\/<\/p>\n\n\n\n

Entwine 是一个 C++ 库，提供用于组织、存储和处理大量点云数据集的工具。它包含一系列用于点云压缩的算法，包括使用 Zstandard 算法进行无损压缩。<\/p>\n\n\n\n

3.灰狗：https:\/\/greyhound.io\/<\/p>\n\n\n\n

Greyhound 是一个 C++ 库和服务器，用于通过 Web 传输点云数据。它包含一系列点云压缩算法，包括使用 Zstandard 算法的无损压缩。<\/p>\n\n\n\n

4.PCL（点云库）：https:\/\/pointclouds.org\/<\/p>\n\n\n\n

PCL 是一个 C++ 库，提供处理和分析点云数据的工具。它包含一系列用于点云压缩的算法，包括使用 LZF 算法进行无损压缩。<\/p>\n\n\n\n

5.CloudCompare：https：\/\/www.cloudcompare.org\/<\/p>\n\n\n\n

CloudCompare 是一款独立应用程序，提供可视化和处理点云数据的工具。它包含一系列点云压缩算法，包括使用 Zstandard 算法的无损压缩。<\/p>\n\n\n\n

6.LASlib：https:\/\/github.com\/LAStools\/LASlib<\/p>\n\n\n\n

LASlib 是一个 C++ 库，用于读取和写入 LAS 格式的 LiDAR 数据。它支持使用 LZF 算法进行无损压缩。<\/p>\n\n\n\n

7.LAStools：https:\/\/rapidlasso.com\/lastools\/<\/p>\n\n\n\n

LAStools 是用于处理 LiDAR 数据的命令行工具集合。它包含一系列用于点云压缩的算法，包括使用 LZF 算法进行无损压缩。<\/p>\n\n\n\n

8. libLAS：https:\/\/liblas.org\/<\/p>\n\n\n\n

libLAS 是一个 C++ 库，提供用于读取、写入和操作 LiDAR 数据的工具。它支持使用 LZF 算法进行无损压缩。<\/p>\n\n\n\n

9.OpenVDB：https:\/\/www.openvdb.org\/<\/p>\n\n\n\n

OpenVDB 是一个用于处理体积数据（包括点云数据）的 C++ 库。它包含一系列用于点云压缩的算法，包括使用 Snappy 算法的无损压缩。<\/p>\n\n\n\n

10.FUSION\/LDV：http:\/\/forsys.cfr.washington.edu\/fusion\/fusionlatest.html<\/p>\n\n\n\n

FUSION 是一个用于处理 LiDAR 数据的软件包，由美国农业部林务局开发。它支持使用 LZW 算法进行无损压缩。<\/p>\n\n\n\n

备注<\/strong> 其中一些库\/工具是独立的软件应用程序，而另一些则是可以与其他软件集成的库。此外，其中一些库\/工具是开源的，而另一些则是专有的。<\/p>\n","protected":false},"excerpt":{"rendered":"

压缩算法：这些算法压缩点云数据以减少存储或传输带宽。<\/p>\n","protected":false},"author":4,"featured_media":6308,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[597],"tags":[477,608,609],"yoast_head":"\nCompression Algorithms - Neuvition | solid-state lidar,lidar sensor suppliers, lidar technology, lidar sensor<\/title>\n<meta name=\"description\" content=\"Compression algorithms: These algorithms compress the point cloud data to reduce storage or transmission bandwidth.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/cdn.neuvition.com\/technology-blog\/compression-algorithms.html\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Compression Algorithms - Neuvition | solid-state lidar,lidar sensor suppliers, lidar technology, lidar sensor\" \/>\n<meta property=\"og:description\" content=\"Compression algorithms: These algorithms compress the point cloud data to reduce storage or transmission bandwidth.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/cdn.neuvition.com\/technology-blog\/compression-algorithms.html\" \/>\n<meta property=\"og:site_name\" content=\"Neuvition | solid-state lidar,lidar sensor suppliers, lidar technology, lidar sensor\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-17T07:00:51+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-07-17T07:00:53+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.neuvition.com\/wp-content\/uploads\/2023\/07\/18.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"300\" \/>\n\t<meta property=\"og:image:height\" content=\"180\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"3 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/cdn.neuvition.com\/technology-blog\/compression-algorithms.html\",\"url\":\"https:\/\/cdn.neuvition.com\/technology-blog\/compression-algorithms.html\",\"name\":\"Compression Algorithms - 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