# Onboard Real-Time Hyperspectral Image Processing System Design for Unmanned Aerial Vehicles

## TL;DR

This paper presents a compact, real-time hyperspectral image processing system for drones that efficiently handles large data volumes.

## Contribution

The novel dual-processor FPGA-ARM architecture enables real-time processing and storage of hyperspectral data on UAVs.

## Key findings

- The system can store over 200 frames per second at 640 × 270 resolution.
- It achieves real-time processing with a 5000-frame task completed in 1000 ms.
- The system weighs 6 kg and consumes 40 W, making it suitable for airborne use.

## Abstract

This study proposes and implements a dual-processor FPGA-ARM architecture to resolve the critical contradiction between massive data volumes and real-time processing demands in UAV-borne hyperspectral imaging. The integrated system incorporates a shortwave infrared hyperspectral camera, IMU, control module, heterogeneous computing core, and SATA SSD storage. Through hardware-level task partitioning—utilizing FPGA for high-speed data buffering and ARM for core computational processing—it achieves a real-time end-to-end acquisition–storage–processing–display pipeline. The compact integrated device exhibits a total weight of merely 6 kg and power consumption of 40 W, suitable for airborne platforms. Experimental validation confirms the system’s capability to store over 200 frames per second (at 640 × 270 resolution, matching the camera’s maximum frame rate), quick-look imaging capability, and demonstrated real-time processing efficacy via relative radio-metric correction tasks (processing 5000 image frames within 1000 ms). This framework provides an effective technical solution to address hyperspectral data processing bottlenecks more efficiently on UAV platforms for dynamic scenario applications. Future work includes actual flight deployment to verify performance in operational environments.