Slice adaptive filtering algorithm based on single-photon laser point cloud density segmentation

Abstract

The invention discloses a slice adaptive filtering algorithm based on single-photon laser point cloud density segmentation. The slice adaptive filtering algorithm comprises the following steps: S1, constructing a spatial region scanning window on original airborne photon point clouds with different spatial densities according to laser scanning time or laser moving distance width and maximum photonelevation as heights; S2, scanning and counting the point cloud density in each spatial region scanning window, and dividing the whole data space into a plurality of spatial regions with different spatial densities; S3, constructing a density relationship among the divided regions based on the densities of the different space density regions, determining different point cloud density thresholds in the regions, and extracting point cloud effective data; and S4, sorting and analyzing the point cloud effective data to realize slice segmentation adaptive filtering of different density region spaces.

Description

technical field [0001] The invention relates to the technical field of model algorithms, in particular to a slice adaptive filtering algorithm based on single-photon laser point cloud density segmentation. Background technique [0002] Single-photon lidar is a new type of laser detection technology developed in recent years. Compared with traditional laser radar, single-photon lidar has a higher pulse transmission repetition rate, and uses extremely sensitive and high-receiving devices, which can detect and accept hundreds of Even the detection of the echo envelope amplitude of thousands of photons is transformed into the detection of a single photon, so it has the advantages of long distance, high repetition frequency, high efficiency, light weight, etc. Low, and the contradiction between pulse energy and repetition frequency. [0003] Single-photon lidar has a big difference in design ideas and data processing methods. When obtaining effective signals, it no longer focus...

AI Technical Summary

Problems solved by technology

The filtering effect of this method is not good, and the filtering results of different density areas are different, such as Figure 3-4 shown

For areas with poor effects, in order to accurately extract effective data, the filtering result is used as the initial value for further subsequent processing, such as spatial density filtering and other algorithms, so the calculation amount of the large number of laser point clouds will be further greatly increased

[0005] For the above-mentioned problems in single-photon data processing, no effective solution has been proposed so far.

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