Hyperspectral Imaging System Market: Navigating Opportunities (2023–2028)
The global hyperspectral imaging systems market is projected to reach USD 42.3 billion by 2027 from USD 18.1 billion in 2022, at a CAGR of 18.5% during the forecast period. Market growth can largely be attributed to factors such as increasing funding and investments in this field and the growing industrial applications of hyperspectral imaging. Emerging markets in developing economies are expected to offer potential growth opportunities for players operating in the market. The hyperspectral imaging systems market is segmented based on product, technology, application, and region.
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The global hyperspectral imaging system market is projected to reach USD 34.3 billion by 2028 from USD 16.8 billion in 2023, at a CAGR of 15.4% during the forecast period. Growing funds and related investments and the untapped opportunities in emerging markets are expected to provide growth opportunities for players during the forecast period.
The hyperspectral imaging system market is highly fragmented and is dominated by various players. The major players operating in this market are Headwall Photonics (the US), Corning Incorporated (US), Specim, Spectral Imaging Ltd. (Finland), Resonon, Inc. (US), and Norsk Elektro Optikk (Norway). These include product launches, contracts, partnerships, mergers and acquisitions, and new product development activities to further expand their presence in the hyperspectral imaging system market.
HEADWALL PHOTONICS (US)
Headwall Photonics develops and offers optical modules and fully integrated imaging devices with unique holographic diffraction gratings. The company provides hyperspectral cameras for applications in defense & security, remote sensing, research, and industrial inspection. For instance, in July 2022, the company acquired Holographix LLC (US), which opened channels to new customers and markets and products and capabilities for existing customers of both companies while expanding the manufacturing capabilities to address future growth.
OPPORTUNITY: AI-based hyperspectral sensing techniques for food, agriculture, and medical applications
During the past two decades, HSI technologies have found numerous successful applications for food and agriculture. Recently, miniature imaging spectrographs/spectrometers, all-in-one small hyperspectral cameras, and snapshot hyperspectral imagers are commercially available, which make it possible to develop compact and portable imaging systems and devices that can be used in confined spaces (e.g., overhead imaging in plant growth chambers) and field applications (e.g., crop health/disease sensing using drones or ground platforms). Integration of AI capabilities through machine learning into hyperspectral imaging systems is becoming a new axis for developing novel smart sensing devices and instruments.
CHALLENGE: Lack of cost-effective super-resolution in the spatial domain
Researchers have applied HIS as a new technique in a variety of fields, including agriculture, aerial and space imagery, ecology, geology, medicine, and industrial inspection. A hyperspectral image has a high resolution in the spectral domain but has a lower resolution in the spatial domain. Atmospheric scattering, secondary illumination, and sensor noise are the factors that impact the hyperspectral image quality. Thus, it is essential for improving spatial resolution for numerous applications in order to utilize this technique in a better way. As replacing hardware (hyperspectral camera units) is expensive, increasing spatial resolution through software is a significant problem that market competitors are currently facing.
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The global hyperspectral imaging system market is segmented into North America, Europe, Asia Pacific, and the Rest of the World. Primarily due to government investments in launching satellites and increased adoption of imaging cameras in defense North America is expected to dominate the market during the forecast period.
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