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Run your analysis now →https://www.patsnap.com/resources/blog/rd-blog/hyperspectral-camera-hardware-and-data-cubes-patent-landscape/ · Patsnap · data cut-off 2026-07-31 · downloaded from the live page
Patent Landscape · Spectroscopy InstrumentsHyperspectral Camera Hardware and Data Cube Patents
- Concentrated but not locked up. the top 5 assignees hold 34.4% of all 346 records in scope, and the top 10 hold 48.0% — leaving over half the field to a long tail of single- and few-filing entrants.
- Filing kept growing after the 2020 peak. the field peaked at 50 records in 2020, then filings from 2021 to 2024 (the last complete year) rose 21%, from 24 to 29.
- Classification and diagnosis dominate the claims. G06T image processing (24.3%), G06V recognition (22.5%) and A61B diagnosis/surgery (22.3%) each touch roughly a fifth to a quarter of all 346 records, while domestic-appliance and wireless classes sit well behind at 11.6% each.
346
Published Records
34%
Top-5 Share of All Records
+21%
Filing Growth 2021→2024
US
Leading Jurisdiction
Filing growth compares 2021 (24 records) with 2024 (29) — a three-year span. 2024 is the most recent year we treat as complete: publication lags filing by roughly 18 months, so 2025 onwards are still filling in and any growth rate that ends there would understate the field. Top-5 share is the combined record count of the five largest assignees divided by all 346 records in scope (CR5), not by the ranked leaders only.
Published byPatsnap Research··7 min readSourced from Patsnap Eureka
Overview
What this landscape covers
This landscape tracks patent activity where hyperspectral camera hardware meets spectral data cube processing — push-broom sensor design, spatial-spectral tradeoffs, illumination uniformity, and the classification models built on top of the resulting data cubes. The scope spans 346 published records filed between 2015 and mid-2026, drawn from a search string that pairs hardware terms with the processing and real-time constraints that define a working system rather than a bench prototype.
Records here sit at the intersection of optics, imaging software and, increasingly, diagnostic and agricultural end-uses — which is why classes as different as A61B (diagnosis and surgery) and F24C (domestic stoves and ranges) both appear with meaningful share. Publication lags filing by roughly 18 months, so counts for 2025 and 2026 are still filling in and should not be read as a slowdown.
Filing activity and technology composition, 2015-2026
Source: Patsnap Eureka. Assignee ranking and totals. Derived from a Patsnap search on Hyperspectral Camera Hardware and Data Cubes covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
The Data
Filing trends and technology composition
Two views of the same 346 records: how filing volume moved year over year, and which IPC subclasses carry the claims. Because a single record can carry several IPC classes, the composition shares add up to more than 100% of the record total.
Filing trend, 2017-2026
Volume ran from 34 records in 2017 to a peak of 50 in 2020, then held in a 21%-growth band from 24 records in 2021 to 29 in 2024 — the last year with complete publication coverage. 2025 and 2026 figures are undercounted by definition and will revise upward.
IPC subclass composition
G06T (image data processing), G06V (image/video recognition) and A61B (diagnosis and surgery) each cover roughly a fifth to a quarter of the 346 records, confirming that most filings pair a hardware sensor claim with a downstream classification or diagnostic application rather than claiming optics alone.
Shares are the percentage of the 346 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Source: Patsnap Eureka. Filing trend and technology composition. Derived from a Patsnap search on Hyperspectral Camera Hardware and Data Cubes covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish.
Go deeper on Hyperspectral Camera Hardware and Data Cubes with Eureka
This page is one run against one query. Ask Eureka your own question about hyperspectral camera hardware and data cubes and every answer comes back with the patent numbers behind it.
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Representative and most-cited filings
Representative recent filing
WO2025104370A1 — Detecting elastane from textile samples
TEKNOLOGIAN TUTKIMUSKESKUS VTT OY
The application, filed by Teknologian Tutkimuskeskus VTT OY, determines a mathematical classification model from the average spectrum of hyperspectral images of textile samples containing elastane, then applies that model to classify elastane content in a second set of textile samples from their hyperspectral images.Published 2025-05-22 — a recent example of the classification-model claim pattern applied to a non-medical, non-food material stream.
Most-cited records in scope
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US20170079530A1 | Reflective mode multi-spectral time-resolved optical imaging methods and apparatuses for tissue classification | 327 |
| 2 | US20220057519A1 | Automated threat detection and deterrence apparatus | 217 |
| 3 | US20160187199A1 | Sensor-synchronized spectrally-structured-light imaging | 206 |
| 4 | WO2015077493A1 | Sensor-synchronized spectrally-structured-light imaging | 206 |
| 5 | US20160327279A1 | Connected food preparation system and method of use | 157 |
| 6 | US20160327281A1 | Connected food preparation system and method of use | 144 |
| 7 | US20170367580A1 | Reflective mode multi-spectral time-resolved optical imaging methods and apparatuses for tissue classification | 139 |
| 8 | US20180310828A1 | Reflective mode multi-spectral time-resolved optical imaging methods and apparatuses for tissue classification | 127 |
| 9 | US20160334276A1 | Apparatuses and methods for BIO-sensing using unmanned aerial vehicles | 121 |
| 10 | WO2017074505A1 | Reflective mode multi-spectral time-resolved optical imaging methods and apparatuses for tissue classification | 101 |
Citation counts are drawn from within this searched corpus and skew toward older filings that have had more time to accumulate citations — read them as a signal of influence on the field, not of current commercial weight.
Each row carries its publication number; clicking a row searches Eureka by that number.
Source: Patsnap Eureka. Citation counts and representative records. Derived from a Patsnap search on Hyperspectral Camera Hardware and Data Cubes covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
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What the numbers mean for filing strategy
Three patterns stand out once the ranking, the trend and the class composition are read together.
Concentration
34.4% / 48.0%
top 5 / top 10 share of 346 records
The top of the field is dense, the rest is open
With the leader alone accounting for 49 records and fifth place holding 11, the gap between the top handful and the rest of the ranked 100 companies is steep. But because the top 10 combined only reach 48.0% of all 346 records, more than half of the field's activity sits with entrants outside that group.
Ranked leaders, not a top-50 or top-100 filter.
Momentum
24 → 29 (+21%)
records, 2021 to 2024
Growth resumed after the 2020 peak
Filing volume peaked at 50 records in 2020, dipped, then climbed 21% from 24 records in 2021 to 29 in 2024, the last year with complete publication coverage. That is a rebuilding trend, not a plateau, and it predates the 18-month publication lag that still masks 2025-2026 volume.
2024 is the most recent complete year.
Composition
24.3% G06T
share of 346 records
Processing claims outnumber pure optics claims
Image-processing (G06T), recognition (G06V) and diagnosis (A61B) subclasses each appear on close to a quarter of records, while the hardware-adjacent domestic-appliance class F24C holds 11.6%. Most active filers are claiming the data pipeline around the sensor, not the sensor in isolation.
Classes overlap; shares sum above 100% of the 346-record base.
Eureka AI Agent
Looking for what nobody has claimed yet?
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to hyperspectral camera hardware and data cubes, with the prior art for and against each one.
Source: Patsnap Eureka. Co-assignee relationships and derived observations. Derived from a Patsnap search on Hyperspectral Camera Hardware and Data Cubes covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
Players
Who is filing, and where activity has gone quiet
The ranked assignee list spans 100 companies, from a single leader at 49 records down to a long tail of one- and two-filing entrants. Momentum data shows even some previously active names recording zero filings in the latest year — consistent with the broader trend of 2025-2026 undercounts, but worth checking record-by-record before reading it as an exit.
Leader
49 records
top-ranked assignee
One filer sets the pace
The leading assignee's 49 records dwarf the fifth-place holder's 11, a gap wide enough that competitive tracking should treat this filer as a distinct category rather than compare it directly against the rest of the ranking.
Compare against the 34.4% top-5 share, not against the leader alone.
Mid-field
11 → 9
5th to 10th place
A tight cluster just below the leader
Fifth place holds 11 records and tenth place holds 9 — a narrow band that suggests several assignees are filing at a similar, moderate pace rather than one clear runner-up emerging.
Top 10 combined: 48.0% of 346 records.
Collaboration
4 pairs
co-assignee pairings identified
Co-filing is rare and concentrated
Only four co-assignee pairs appear across the dataset, with one individual pairing filing together nine times — far above the other pairs, which each show one or two joint records. Co-development is the exception here, not the norm.
Strongest pair: 9 joint records.
Recent-year filing momentum by assignee
| Assignee | Recent year | YoY |
|---|---|---|
| June Life, Inc. | 0 | — |
| Spectral MD, Inc. | 0 | — |
| Koninklijke Philips N.V. | 0 | — |
| Hangzhou Zero Zero Technology Co., Ltd. | 0 | — |
| MAXAR INTELLIGENCE INC | 0 | — |
| ZASS RON | 0 | — |
| Canadian Space Agency | 0 | — |
| Apeel Technology, Inc. | 0 | — |
Source: Patsnap Eureka. Assignee-level momentum. Derived from a Patsnap search on Hyperspectral Camera Hardware and Data Cubes covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
What's Next
Where to take this next
The dataset points to two practical follow-ups: checking whether a specific claim scope is already occupied, and testing a filing idea against what the leaders have already locked down.
Run a freedom-to-operate check on a specific sub-area
Illumination uniformity, push-broom scan calibration and on-sensor compression show thinner coverage than the recognition and diagnosis clusters — worth a targeted search before committing claim language.
Explore this in Eureka →Map the leader's claim boundaries before filing nearby
With one assignee holding 49 of 346 records, understanding exactly what that portfolio blocks is a prerequisite for filing anywhere near its core claims.
Analyze portfolios in Eureka →Source: Patsnap Eureka. Forward-looking reading of the same dataset. Derived from a Patsnap search on Hyperspectral Camera Hardware and Data Cubes covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
FAQ
Common questions about this landscape
This dataset covers 346 published records filed between 2015 and mid-2026 that match hyperspectral camera hardware and spectral data cube terms alongside processing constraints like push-broom scanning, illumination uniformity or real-time classification. The true global figure is larger, since this scope is defined by a specific search string rather than every patent that touches hyperspectral imaging broadly. Filing counts for 2025 and 2026 are understated because publication lags filing by roughly 18 months.
The ranked list covers 100 companies, with the leading assignee holding 49 records and a steep drop to 11 records at fifth place. The top 5 assignees together account for 34.4% of all 346 records, and the top 10 account for 48.0% — meaning slightly over half of all filing activity comes from outside the top 10. This is a concentrated-but-not-locked field: a strong leader, a moderate mid-tier cluster, and a long tail of one- or two-filing entrants.
Filings peaked at 50 records in 2020, and the most recent complete year-over-year comparison shows growth of 21%, from 24 records in 2021 to 29 in 2024. 2025 and 2026 figures in the raw trend look lower, but that reflects publication lag rather than an actual slowdown, since patent applications typically take about 18 months to appear in public databases. Based on the 2021-2024 trend, the underlying filing rate was still rising as of the last complete year.
The dominant IPC classes are G06T (image data processing, 24.3% of the 346 records), G06V (image and video recognition, 22.5%) and A61B (diagnosis and surgery, 22.3%), followed closely by G01N (material analysis, 19.1%) and G06K (data recognition, 17.9%). Because a single patent can be classified under multiple IPC codes, these percentages add up to well over 100% of the record base — they describe overlap, not a strict breakdown. The pattern shows most filers claim the processing or application layer built on top of the sensor, not just the optical hardware.
WO2025104370A1, filed by Teknologian Tutkimuskeskus VTT OY and published 2025-05-22, covers a method for building a mathematical classification model from the average spectrum of hyperspectral images of textile samples containing elastane, then applying that model to classify elastane content in new textile samples. It is a representative example of the classification-model claim pattern seen across the dataset, applied here to a textile material stream rather than food or medical tissue. Anyone building hyperspectral classification tools for fiber or textile composition analysis should review this filing's exact claim scope before designing a similar pipeline.
Answers are grounded in the same dataset. Derived from a Patsnap search on Hyperspectral Camera Hardware and Data Cubes covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
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Disclaimer. This page is generated from Patsnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.
Patent data carries inherent limitations: recent filings (typically the most recent 18–24 months) are under-counted due to standard publication lag; counts may be reported at either a patent-family or a patent-record basis and are not always directly comparable; classification, applicant-name, and citation data may contain errors, duplicates, or omissions; and the underlying search query defines and constrains the scope shown. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
Nothing on this page constitutes an exhaustive prior-art, novelty, freedom-to-operate, or validity search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. Any patent, commercial, or strategic decision should be verified independently and reviewed with qualified patent, legal, and domain professionals. Patsnap makes no warranties, express or implied, as to the accuracy, completeness, or fitness for any particular purpose of the information presented.
Machine translation. Assignee and organisation names originally recorded in Chinese, Japanese or Korean have been rendered into English by an AI translation step so that the tables stay readable. These renderings are best-effort and may not match a company's registered English name; the original name is what the underlying patent record carries, and it is what any Eureka query launched from this page uses.