AI-Driven HSI: Multimodality, Fusion, Challenges, and the Deep Learning Revolution

TL;DR

This paper reviews hyperspectral imaging (HSI), emphasizing its integration with deep learning and multimodal fusion to enhance analysis, address challenges, and explore emerging applications like LLM-based systems, highlighting industry trends and future directions.

Contribution

It provides a comprehensive overview of HSI advancements, focusing on deep learning integration, multimodal fusion, and emerging applications such as highbrain LLMs, offering insights into industry growth and challenges.

Findings

Deep learning improves feature extraction and classification accuracy in HSI.

Fusion of hyperspectral data with LLMs enables advanced applications like crash detection.

HSI industry shows significant growth and technological innovation.

Abstract

Hyperspectral imaging (HSI) captures spatial and spectral data, enabling analysis of features invisible to conventional systems. The technology is vital in fields such as weather monitoring, food quality control, counterfeit detection, healthcare diagnostics, and extending into defense, agriculture, and industrial automation at the same time. HSI has advanced with improvements in spectral resolution, miniaturization, and computational methods. This study provides an overview of the HSI, its applications, challenges in data fusion and the role of deep learning models in processing HSI data. We discuss how integration of multimodal HSI with AI, particularly with deep learning, improves classification accuracy and operational efficiency. Deep learning enhances HSI analysis in areas like feature extraction, change detection, denoising unmixing, dimensionality reduction, landcover mapping, data augmentation, spectral construction and super resolution. An emerging focus is the fusion of hyperspectral cameras with large language models (LLMs), referred as highbrain LLMs, enabling the development of advanced applications such as low visibility crash detection and face antispoofing. We also highlight key players in HSI industry, its compound annual growth rate and the growing industrial significance. The purpose is to offer insight to both technical and non-technical audience, covering HSI's images, trends, and future directions, while providing valuable information on HSI datasets and software libraries.