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‘More than just an image’: Purdue tech extracts hyperspectral info from conventional photos

09.10.25 | Purdue University

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WEST LAFAYETTE, Ind. — Professionals in agriculture, defense and security, environmental monitoring, food quality analysis, industrial quality control, and medical diagnostics could benefit from a patent-pending innovation that opens new possibilities of conventional photography for optical spectroscopy and hyperspectral imaging.

Young Kim , Purdue University professor, University Faculty Scholar and Showalter Faculty Scholar, and postdoctoral research associate Semin Kwon of the Weldon School of Biomedical Engineering created an algorithm that recovers detailed spectral information from photographs taken by conventional cameras. The research combines computer vision, color science and optical spectroscopy.

“A photograph is more than just an image; it contains abundant hyperspectral information,” Kim said. “We are one of the pioneering research groups to integrate computational spectrometry and spectroscopic analyses for biomedical and other applications.”

A paper about the team’s research has been published in the peer-reviewed journal IEEE Transactions on Image Processing.

Kim disclosed the innovation to the Purdue Innovates Office of Technology Commercialization , which has applied for a patent to protect the intellectual property. Industry partners interested in developing or commercializing the algorithm should contact Patrick Finnerty, assistant director of business development and licensing — life sciences, at pwfinnerty@prf.org about track codes 70097, 70251, 70322 and 70335.

Kwon said the work emphasizes recovering the arbitrary spectrum of a sample rather than solely relying on specific data-driven learning or pretrained algorithms, which excel only in preset tasks and samples.

The team’s method uses an algorithmically designed color reference chart and device-informed computation to recover spectral information from RGB values acquired using conventional cameras, such as off-the-shelf smartphones.

“Importantly, the spectral resolution — around 1.5 nanometers — is highly comparable to that of scientific spectrometers and hyperspectral imagers,” Kwon said. “Scientific-grade spectrometers have fine spectral resolution to distinguish narrow spectral features. This is critical in applications like biomedical optics, material analysis and color science, where even small wavelength shifts can lead to different interpretations.”

Kim said one advantage the Purdue method has over traditional technology is its algorithmic generalizability.

“From an algorithmic standpoint, to the best of our knowledge, our paper presents the first computational spectrometry method with 1.5-nm spectral resolution using a photograph of an arbitrary sample without relying on specific training data or predetermined algorithms,” he said.

Kwon said another advantage of the Purdue method is its hardware simplicity.

“Many mobile spectrometers require additional accessories and bulky components as mandatory attachments to smartphones,” he said. “In contrast, our method leverages the built-in camera of the smartphone. We envision that our general computational photography spectrometry will change how industry uses smartphones.”

Kim and Kwon are currently using the algorithm as a foundation for digital and mobile health applications in both domestic and resource-limited settings.

“Photography is central to these applications, but color distortion has posed a persistent challenge, which is why we are focusing on these settings,” Kim said. “This algorithm provides a basis for quantifying and correcting colors, enhancing the reliability of medical diagnostics.”

The Purdue Innovates Office of Technology Commercialization operates one of the most comprehensive technology transfer programs among leading research universities in the U.S. Services provided by this office support the economic development initiatives of Purdue University and benefit the university’s academic activities through commercializing, licensing and protecting Purdue intellectual property. In fiscal year 2024, the office reported 145 deals finalized with 224 technologies signed, 466 invention disclosures received, and 290 U.S. and international patents received. The office is managed by the Purdue Research Foundation, a private, nonprofit foundation created to advance the mission of Purdue University. Contact otcip@prf.org for more information.

Purdue University is a public research university leading with excellence at scale. Ranked among top 10 public universities in the United States, Purdue discovers, disseminates and deploys knowledge with a quality and at a scale second to none. More than 107,000 students study at Purdue across multiple campuses, locations and modalities, including more than 58,000 at our main campus locations in West Lafayette and Indianapolis. Committed to affordability and accessibility, Purdue’s main campus has frozen tuition 14 years in a row. See how Purdue never stops in the persistent pursuit of the next giant leap — including its integrated, comprehensive Indianapolis urban expansion; the Mitch Daniels School of Business; Purdue Computes; and the One Health initiative — at https://www.purdue.edu/president/strategic-initiatives .

Media contact: Steve Martin, sgmartin@prf.org

IEEE Transactions on Image Processing

10.1109/TIP.2025.3597038

Hyperspectral Information Extraction With Full Resolution From Arbitrary Photographs

19-Aug-2025

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Steve Martin
Purdue Research Foundation
sgmartin@prf.org

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APA:
Purdue University. (2025, September 10). ‘More than just an image’: Purdue tech extracts hyperspectral info from conventional photos. Brightsurf News. https://www.brightsurf.com/news/LQ4VR658/more-than-just-an-image-purdue-tech-extracts-hyperspectral-info-from-conventional-photos.html
MLA:
"‘More than just an image’: Purdue tech extracts hyperspectral info from conventional photos." Brightsurf News, Sep. 10 2025, https://www.brightsurf.com/news/LQ4VR658/more-than-just-an-image-purdue-tech-extracts-hyperspectral-info-from-conventional-photos.html.