Adaptive Band Selection Strategies for Hyperspectral Image Reconstruction in Multi-Agent Autonomous Navigation
Keywords:
hyperspectral imaging; band selection; multi-agent systems; autonomous navigation; image reconstruction; adaptive strategies; cyber-physical infrastructure; spectral compression; distributed perception; governanceAbstract
Hyperspectral imaging offers rich spectral information critical for environmental perception in autonomous navigation, yet the high dimensionality of such data poses substantial computational and communication burdens for multi-agent systems. This paper investigates adaptive band selection strategies that enable efficient hyperspectral image reconstruction across a distributed network of autonomous agents. We examine the structural trade-offs between spectral fidelity, reconstruction accuracy, and bandwidth constraints, proposing a system-level framework that integrates online band prioritization with collaborative reconstruction protocols. The analysis spans several methodological families, including information-theoretic criteria, deep reinforcement learning, and spectral clustering, each evaluated for their scalability and robustness under dynamic operating conditions. Particular attention is given to the infrastructure requirements for deploying such strategies in heterogeneous fleets of vehicles, including communication latency, energy consumption, and onboard computational resources. We further explore the governance and policy implications of spectral data sharing, including fairness in resource allocation and privacy considerations. Sustainability is addressed through the lens of reducing redundant transmissions while maintaining high reconstruction quality. By synthesizing insights from signal processing, multi-agent coordination, and socio-technical system design, this paper provides a comprehensive perspective on how adaptive band selection can balance performance and operational constraints. The findings underscore the necessity of context-aware, resilience-oriented architectures that can respond to changing environmental and mission conditions without centralized oversight.
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This article is published under the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
