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Hardware accelerated compression of LIDAR data using FPGA devices.

Anton Biasizzo1, Franc Novak

  • 1Jozef Stefan Institute, Jamova 39, Ljubljana 1000, Slovenia. anton.biasizzo@ijs.si

Sensors (Basel, Switzerland)
|May 16, 2013
PubMed
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This study presents a hardware-accelerated method for compressing airborne Light Detection and Ranging (LIDAR) data. This approach significantly speeds up data processing and reduces storage needs for detailed terrain mapping.

Area of Science:

  • Geospatial Science
  • Computer Engineering
  • Data Compression

Background:

  • Airborne Light Detection and Ranging (LIDAR) is crucial for detailed terrain mapping.
  • High sampling density in LIDAR generates large datasets, demanding significant storage and processing power.
  • The LAS format is the standard for storing and exchanging LIDAR data.

Purpose of the Study:

  • To develop and present a hardware-accelerated compression method for airborne LIDAR data.
  • To improve the efficiency of LIDAR data storage and processing.
  • To reduce the computational load associated with large LIDAR datasets.

Main Methods:

  • Implementation of a dedicated FPGA-based circuit for LIDAR data compression and decompression.
  • Interfacing the hardware compressor to a computer via a PCI-E bus.

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  • The hardware compressor comprises three modules: LIDAR data predictor, variable length coder, and arithmetic coder.

    • Main Results:

    • Hardware-accelerated compression demonstrates significantly faster performance compared to software-based methods.
    • The FPGA-based approach effectively reduces the storage requirements for LIDAR data.
    • Processor load is alleviated due to the offloading of compression tasks to dedicated hardware.

    Conclusions:

    • Hardware acceleration offers a viable solution for efficient LIDAR data compression.
    • This method enhances the practicality of using high-density LIDAR data for mapping and analysis.
    • The developed FPGA circuit provides a substantial improvement in processing speed and resource utilization.