Hyperspectral Imaging System Market: Navigating Opportunities (2023–2028)
The global hyperspectral imaging systems market is projected to reach
$34.3 billion by 2028, growing at a CAGR of 15.4% from 2023 to 2028
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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