1. Key Raw Materials Suppliers and Price Analysis
Major suppliers of hyperspectral camera raw materials include the following companies: Costar Technologies, Lumentum Holdings Inc, Broadcom Inc, LG Innotek, Sunny Optical Technology and OMNIVISION.
Table Key Raw Materials Suppliers Analysis
Raw Material | Suppliers | Contact Information |
Electronic components | Costar Technologies | Web: costartechnologies.com Tel: 469-635-6800 Add: 101 Wrangler Drive, Ste 201, Coppell, TX 75019 |
OMNIVISION | Web: www.ovt.com Tel: +1 408 567 3000 Add: 4275 Burton Drive, Santa Clara, California 95054, USA | |
Optical chips | Lumentum Holdings Inc | Web: www.lumentum.com Tel: 408 546 5483 Add: 1001 Ridder Park Drive, San Jose, CA 95131, USA |
Broadcom Inc | Web: www.broadcom.com Tel: 650-427-6000 Add: 3421 Hillview Ave, Palo Alto, California, 94304, USA | |
Camera modules | LG Innotek | Web: www.lginnotek.com Tel: +82-2-3777-1114 Add: Building E1/E3, 30, Magokjungang 10-ro, Gangseo-gu, Seoul, Republic of Korea |
Sunny Optical Technology | Web: www.sunnyoptical.com Tel: 0086-574-62538080 Add: 27-29 Shunke Road, Yuyao, Zhejiang, China |
The cost of producing a camera lens is affected by a variety of factors, including the complexity of the design, the materials used, and the manufacturing process. The cost of producing camera lenses varies depending on the lens type and manufacturer. High-end lenses with advanced features and materials can cost thousands of dollars to produce, while entry-level lenses can cost hundreds. Cost analysis of lens materials is an important factor in determining the overall cost of producing a camera lens. The cost of lens materials can vary greatly depending on the type of lens being produced and the quality of the materials used. For example, high-end lenses may use exotic materials such as fluorite or ED glass, which can significantly increase the cost of production. Devices with embedded cameras contain raw materials including silicon and plastic, as well as rare earth minerals like gold and lithium. Advances in technology have made it possible to produce lenses more efficiently and at lower cost. For example, some manufacturers are using 3D printing to produce lens elements, which can reduce the cost and time required for manufacturing.
2. Major Distributors of Hyperspectral Cameras Analysis
Key distributors of hyperspectral camera include Channel Systems Inc. (CSI), Tech Imaging Services, Quantum Design Europe, STEMMER IMAGING, Konica Minolta and DATVISION.
Their service coverage covers North America, Europe, and Asia. Through these distribution networks, hyperspectral camera manufacturers are able to effectively market their products to global markets for multiple downstream applications such as industrial, agricultural, medical, and environmental monitoring.
Table Downstream Distributors
Downstream Distributors | Contact Information |
Channel Systems Inc. (CSI) | Web: channelsystems.ca Tel: 204.753.5190 Add: W.B. Lewis Business Centre Suite 2, 24 Aberdeen Avenue, Pinawa MB Canada R0E 1L0, Canada |
Tech Imaging Services | Web: techimaging.com Tel: 978-740-0063 Add: 428 Lincoln Avenue, Saugus, MA 01906, USA |
Quantum Design Europe | Web: qd-europe.com Tel: +49 6157 80710-0 Add: Breitwieserweg 9, 64319 Pfungstadt, Germany |
STEMMER IMAGING | Web: www.stemmer-imaging.com Tel: +49 89 80902-0 Add: Gutenbergstr. 9-13, 82178 Puchheim, Germany |
Konica Minolta | Web: www.konicaminolta.com Tel: +81-3-6250-2111 Add: JP TOWER, 2-7-2 Marunouchi, Chiyoda-ku, Tokyo 100-7015, Japan |
DATVISION | Web: www.datvision.co.kr Add: Room 402, Star Valley, 99 Digital-ro 9-gil, Geumcheon-gu, Seoul, South Korea |
3. Major Downstream Buyers of Hyperspectral Cameras Analysis
Key customers of hyperspectral camera include Cargill, ADM, Cleveland Clinic, Mayo Clinic, SHIMADZU CORPORATION, SGS S.A, Eurofins Scientific and Honeywell International.
Table Downstream Buyers
Downstream Buyers | Contact Information |
Cargill | Web: www.cargill.com Tel: 800-227-4455 Add: PO Box 9300, Minneapolis, MN, 55440-9300, USA |
ADM | Web: www.adm.com Tel: +1 312-634-8100 Add: 77 W Wacker Dr #4600, Chicago, IL 60601, USA |
Cleveland Clinic | Web: my.clevelandclinic.org Tel: 216.444.2200 Add: 9500 Euclid Ave., Cleveland , Ohio 44195, USA |
Mayo Clinic | Web: www.mayoclinic.org Tel: 480-301-8000 Add: 13400 E. Shea Blvd., Scottsdale, AZ 85259, USA |
SHIMADZU CORPORATION | Web: www.shimadzu.com Tel: +81-75-823-1111 Add: 1, Nishinokyo Kuwabara-cho, Nakagyo-ku, Kyoto 604-8511, Japan |
Honeywell International | Web: www.honeywell.com Tel: (877) 841-2840 Add: 855 S Mint St, Charlotte, NC 28202, USA |
SGS S.A. | Web: www.sgs.com Tel: +41 22 739 91 11 Add: 1 Place des Alpes, P.O. Box 2152, 1211, Geneva, Switzerland |
Eurofins Scientific | Web: www.eurofins.com Tel: +352 26 18 53 20 Add: Val Fleuri 23, 1526, Luxembourg |
4. Hyperspectral Cameras Market Drivers
‘Advantages of Hyperspectral Cameras’
Hyperspectral imaging provides enhanced per-pixel information, making it particularly valuable when distinguishing objects or materials with similar colors. Hyperspectral imaging can be used in a wide range of applications, including quality control (wood, textiles, paper, building materials, pharmaceuticals), process control (films, moisture content, color), sorting (food, recyclable materials, minerals), remote sensing (ocean color, environmental monitoring, agriculture) and various others. With advances in compact, cost-effective, and powerful hyperspectral imaging systems, the technology can be used in a variety of environments and across platforms, from microscopes to aircraft.
Hyperspectral cameras are advanced imaging devices designed to scan a variety of wavelengths, including visible, ultraviolet, and near-infrared spectra. They are exceptionally durable and cost-effective while delivering exceptional accuracy, minimal distortion, low stray light, and superior image quality. Hyperspectral cameras can obtain continuous spectral information and spatial information of targets, which makes them excellent at identifying and classifying targets. Hyperspectral cameras can be used in a variety of applications such as environmental monitoring, agriculture, medicine, etc. It can detect and analyze the chemical composition, physical properties, and spatial distribution of targets, thereby providing useful information for various applications. Hyperspectral cameras typically have high sensitivity and accuracy, which allows them to detect and analyze weak spectral features and subtle changes in targets. Hyperspectral cameras can acquire and process data in real time and can transmit data remotely, making data acquisition and processing more convenient and faster.
‘Government and private companies provide more investment support’
Governments provide financial support for R&D activities related to hyperspectral imaging. Funding programs and grants are available to academic institutions, research organizations, and companies engaged in developing innovative hyperspectral imaging technologies. In addition, governments form partnerships with private companies to support the development and deployment of these systems. These partnerships involve joint funding, sharing of resources and expertise, and collaboration on R&D projects.
Canadian hyperspectral imaging satellite company, Wyvern, has received a CAD $4M investment from Sustainable Development Technology Canada (SDTC). The investment is tied to a 3-year project that includes support from xarvio® Digital Farming Solutions, a brand of BASF Digital Farming GmbH. Wyvern, a space data company offering affordable and easy-to-access high-resolution hyperspectral imagery, secured an additional USD $7M of funding led by Uncork Capital, with key investors including MaC Venture Capital and Y Combinator. With the new capital, Wyvern’s first three satellites are fully funded, providing certainty to customers with an interest in purchasing the limited remaining capacity. Metaspectral, a software company advancing computer vision using deep learning and hyperspectral imagery, has completed a $4.7 million seed round from SOMA Capital, Acequia Capital, the Government of Canada, and multiple notable angel investors including Jude Gomila and Alan Rutledge.
5. Hyperspectral Cameras Market Challenges
‘Not enough portability’
Traditional hyperspectral imaging systems based on separate spectrometers and cameras are bulky and cumbersome, making them difficult to move frequently or fit into small spaces. At the same time, due to its data processing complexity and real-time requirements, the real-time performance and portability of hyperspectral cameras are also subject to certain limitations. Existing hyperspectral cameras can only scan one line at a time, primarily due to their design and mechanical moving components that limit frame rates. This limitation makes this technology unsuitable for time-critical applications and requires further research. Existing commercial greenhouse phenotyping systems are also often too large. Additionally, high-power halogen lamps commonly used for hyperspectral reflectance imaging generate large amounts of heat, which is not ideal for illuminating tender plants at close range. Recently, all-in-one small hyperspectral cameras have been introduced to the market, making it possible to develop compact imaging systems.
‘Lack of a common standard for manufacturing of hyperspectral sensors’
A hyperspectral imaging system is a significant investment, and most users will use the chosen instrument for many years and perform a large amount of scientific work based on the instrument data. Despite having a high level of expertise in spectroscopy or hyperspectral data processing, many users still have limited knowledge of hyperspectral instrument hardware. Coupled with the lack of a common industry standard for measuring and recording these instruments, it can often result in requirements specifications that do not correctly differentiate between different instruments when it comes to many of the subtler technical parameters that are more important than the actual parameters. Therefore, in many cases, price becomes the main discriminating factor. This may not always give the best decision from the user’s perspective. The consequences of such a decision often become apparent only after a considerable period of use of the instrument, and it is subsequently impossible to change the decision.
‘Insufficient labeled data for training, and the high volume of produced data’
During data collection, the redundancy of continuous spectral bands results in the availability of spatially and spectrally duplicated information, hindering optimal and discriminative retrieval of spatial spectral features. Collected hyperspectral data sets contain noisy bands that cannot be used due to acquisition errors, resulting in a loss of information on spectral features. Due to poor resolution, each pixel encompasses a vast spatial area on the Earth’s surface, thus introducing inconsistencies and uncertainties to the classification algorithms employed. Airborne spectrometers cover a much smaller area and therefore can only collect a limited amount of hyperspectral data. This results in a limitation in the number of training samples for classification models. HSI usually contains classes corresponding to a single scene, and the learning process of available classification models requires labeled data. However, labeling each pixel requires human skills, which is arduous and time-consuming. Additionally, there is currently a lack of open source imaging spectroscopy software tools and packages. The large amounts of data produced by hyperspectral sensors become difficult to store, transmit, process, and understand. The average hyperspectral image is nearly 100 times larger in size than a conventional RGB camera image of the same land area, requiring specialized methods to process it efficiently.
