Thermal Imaging Signal Processing Patents: Leader & Long Tail 2026
- One assignee dominates. The leading company holds 11 of the 19 records in the assignee ranking, against a fifth-place filer with just 1 — a steep drop rather than an even spread.
- Filing activity peaked in 2023. Records rose to 8 in that year from a single filing in 2017, though the two most recent years are understated by publication lag.
- Claims cluster in two IPC subclasses. G06T (image data processing) and H04N (pictorial communication) cover 78.9% and 57.9% of the 19 records respectively, leaving diagnostic and recognition-adjacent classes thinly filed.
What this landscape covers
Thermal imaging signal processing spans the algorithms that turn raw microbolometer or cooled-detector output into a usable image: non-uniformity correction to remove fixed pattern noise, shutterless calibration, dynamic range compression for display, and detail enhancement that preserves radiometric accuracy. This dataset tracks 19 published records filed between 2015 and 2026 that combine thermal image processing or non-uniformity correction terms in the title/abstract with claim-level language on fixed pattern noise, shutterless correction, dynamic range compression, detail enhancement, radiometric accuracy or frame rate limits.
The scope is narrow by design: it isolates the signal-processing layer of thermal imaging rather than the optics, detector hardware or broader computer-vision applications that sit around it. That narrowness is why the assignee count is small and why a single filer can account for more than half the ranked records.
Filing trend and technology mix
The two charts below use the full 19-record dataset: one tracks filings by year, the other breaks the same records down by IPC subclass. Because a single record can carry more than one classification, the subclass shares sum to well over 100%.
Filings by year, 2015-2026
Activity was sparse before 2023, when filings reached their peak of 8 for the period. 2025 and 2026 figures will revise upward as publication catches up with filing dates, so read the tail of this chart as a floor, not a ceiling.
Records by IPC subclass (share of 19 records)
G06T and H04N together account for most of the corpus, consistent with a field centred on image data processing and video/broadcast pictorial communication. A61B (diagnosis and surgery) and G06K (data recognition) each sit at 15.8% of records, marking smaller but distinct application branches rather than noise.
Shares are the percentage of the 19 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Thermal Imaging Signal Processing with Eureka
This page is one run against one query. Ask Eureka your own question about thermal imaging signal processing and every answer comes back with the patent numbers behind it.
Try EurekaThe most-cited filings in this corpus
US20090257679A1 — Scene based non-uniformity correction systems and methods
Systems and methods provide scene-based non-uniformity correction for infrared images. One embodiment stores a template frame of infrared pixel data, receives an input frame, determines frame-to-frame motion between the two, warps the template frame accordingly, and compares pixel data to determine irradiance differences used to correct fixed pattern noise without a mechanical shutter.Filed by Teledyne FLIR; cited 75 times within this corpus, the highest count of any record in scope.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US20090257679A1 | Scene based non-uniformity correction systems and methods | 75 |
| 2 | US7995859B2 | Scene based non-uniformity correction systems and methods | 40 |
| 3 | CN109859148A | 红外热图像处理方法及装置 | 7 |
| 4 | WO2015061128A1 | Medical thermal image processing for subcutaneous detection of veins, bones and the like | 6 |
| 5 | WO2009129245A2 | Scene based non-uniformity correction systems and methods | 6 |
| 6 | US20150324956A1 | Medical Thermal Image Processing for Subcutaneous Detection of Veins, Bones and the Like | 1 |
Citation counts are drawn from within this searched corpus and favour older filings that have simply had longer to accumulate citations — treat them as a signal of influence on the field, not of current commercial relevance.
Patent titles are shown in the language they were filed in, not translated, so that each record stays verifiable against the original filing — a translated title will not match in Eureka or in any national register. Publication numbers are shown where the record carries one (6 of 6 rows); clicking a row searches Eureka by that number.
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Three patterns in this dataset matter more than the raw counts: where citation weight sits, how concentrated ownership is, and where the technology composition data points to open ground.
Shutterless correction prior art is dense at the core
The two most-cited records in this corpus, both scene-based non-uniformity correction filings from the same assignee, together account for 115 citations. Any new shutterless or scene-based correction claim will be examined against this pair first.
One company holds most of the ranked records
The leading assignee's 11 records against a fifth-place count of 1 is a steep drop-off, not a gradual one. That concentration is a reason to check freedom-to-operate against this filer specifically before assuming the field is open.
Medical and recognition applications are thinner than core imaging
G06T and H04N carry most of the filing weight, while A61B and G06K each sit at 15.8% of the 19 records and G01J (radiation measurement) at 10.5%. These smaller branches have far less claim density to design around.
Activity peaked in 2023, then the record thins
Filings built steadily from a single record in 2017 to 8 in 2023. The 2025-2026 counts are not yet a reliable read on real activity because publication typically lags filing by around 18 months.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to thermal imaging signal processing, with the prior art for and against each one.
Who is filing, and where the field is still open
The assignee ranking returned by this dataset covers 5 companies — the entire set the data endpoint returns for this search, not a top-50 or top-100 cut. Momentum in the most recent year is flat across all five: none show filings in the latest year, consistent with the publication-lag effect on recent data.
Teledyne FLIR anchors the corpus
Filing under both a corporate entity and a named inventor co-assignment, this group holds the majority of ranked records, including the two highest-cited filings in the dataset, both on scene-based non-uniformity correction.
One recurring inventor-assignee pairing
The strongest co-assignee link in the data pairs the leading corporate filer with a named individual inventor across 2 records, suggesting a specific inventor group behind a portion of the portfolio rather than a broad internal team.
Smaller filers hold single, narrow positions
Beyond the leader, the remaining four ranked assignees each hold small counts, down to a single record at fifth place. This is a long-tail structure: a handful of specific claims rather than broad competing portfolios.
| Assignee | Recent year | YoY |
|---|---|---|
| Axis AB | 0 | — |
| Teledyne FLIR, LLC | 0 | — |
| BAE Systems Information and Electronic Systems Integration Inc. | 0 | — |
| HOGASTEN NICHOLAS | 0 | — |
| Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences | 0 | — |
Where to take this analysis
This landscape identifies concentration and gaps; turning that into a filing or freedom-to-operate position needs claim-level review.
Check freedom-to-operate against the leading assignee
With 11 of 19 ranked records under one filer, including both top-cited patents, a new shutterless or scene-based correction claim should be checked against that portfolio specifically before drafting.
Explore assignee portfolios in EurekaDraft into the under-claimed branches
A61B, G06K and G01J combinations carry far fewer records than G06T/H04N alone, which is where a narrower first claim has more room to clear prior art.
Run a white space search in EurekaCommon questions on thermal imaging signal processing patents
Within this 19-record dataset, one assignee — Teledyne FLIR — holds 11 of the records in the 5-company assignee ranking, well ahead of the fifth-ranked filer at 1 record. This includes the two most-cited filings in the corpus, both on scene-based non-uniformity correction. That concentration means a new entrant should review this filer's claims closely before drafting in the same correction methods, rather than assuming the field is fragmented.
Non-uniformity correction (NUC) is the signal-processing step that removes fixed pattern noise caused by pixel-to-pixel sensitivity differences in uncooled microbolometer arrays. Patent claims in this space split mainly between shutter-based correction, which periodically blocks the scene with a known reference, and shutterless or scene-based correction, which estimates the correction from motion between successive frames. The most-cited record in this dataset, US20090257679A1, describes the latter approach using frame-to-frame motion and template warping.
This dataset contains 19 published records filed or published between 2015 and 2026 that match thermal image processing and non-uniformity correction search terms combined with claim-level language on fixed pattern noise, dynamic range compression, detail enhancement or radiometric accuracy. Filing activity rose from a single record in 2017 to a peak of 8 in 2023, and figures for the two most recent years are understated because publication typically lags filing by around 18 months.
The dataset's IPC composition shows G06T (image data processing and generation) at 78.9% of the 19 records and H04N (pictorial communication) at 57.9%, confirming the field sits primarily in general image processing and video transmission. Smaller but distinct overlaps appear with A61B (diagnosis and surgery, 15.8%), G06K (data recognition, 15.8%), G01J (radiation and light measurement, 10.5%) and G06V (image/video recognition, 5.3%), each pointing to a narrower application context such as medical thermal imaging or automated recognition.
The classes with the lowest record shares in this dataset — A61B, G06K, G01J and G06V — carry far less filing density than the dominant G06T/H04N combination, which suggests less occupied claim space around medical, recognition and radiation-measurement applications of thermal signal processing. A first claim combining a correction technique such as shutterless NUC with one of these thinner application areas, for example diagnostic dynamic range compression, has more room to clear prior art than a claim filed purely in general-purpose image processing.
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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.