Hyperspectral imaging applications

Resonon hyperspectral imaging systems enable you to accurately and consistently distinguish between similar colors or materials. Our systems are in use worldwide on platforms ranging from airplanes to microscopes. As the following examples demonstrate, our solutions solve a wide range of problems.

Resonon's hyperspectral imaging systems are used in agriculture research all over the world, enabling identification of weeds, monitoring of plant health, and evaluation of ripeness. Early detection of crop stress is a common application.

Examples of precision agriculture with hyperspectral imaging are:

Invasive Weed Mapping

A Resonon airborne hyperspectral imaging system was used to identify and locate an invasive weed infestation.

Published in: S.C. Jay et al., Geoscience and Remote Sensins Symposium (IGARSS), 2010

Hyperspectral Fluorescence in Grapevine

A Resonon Pika L hyperspectral imager was used to quantify chlorophyll and nitrogen in Cabernet Sauvignon grapevines. 

Published in Z. Yang et al., Plant Phys. and Biochem. 166, 723 (2021).

Water Stress of Oilseed Rape Leaves (Brassica napus L.).

A Resonon laboratory hyperspectral system was used to detect water stress of oilseed rape leaves (Brassica napus L.).
Published in: Xia Ji'An et al., Comp. and Elec. in Ag. 159, 59 (2019).

Hyperspectral Analysis of Stomatal Behavior of Wheat

A Resonon Pika XC2 hyperspectral camera was used to analyze the stomatal behavior of winter wheat. 
Published in: K. Zhu et al., SPRS J. Phot. and Remote Sens. 168, 197 (2020).

Examples of environmental monitoring are:

Forest Fire Analysis

A Pika NIR camera was used to study the structure and temperatures of a wildfire burning in the Bridger Mountain Range approximately 3 miles from the Resonon facility. The fire burned over 11,000 acres and destroyed 28 homes, but thankfully, no one was injured.

Environmental Mapping with Robotic Teams

An autonomous robotic team was developed that can rapidly learn the characteristics of environments it has never seen before using a Pika XC2. This study describes the characterization of an aquatic environment over just a few minutes.

Phototrophic Microbial Communities

A group at the Max Planck Institute in Germany used a Resonon hyperspectral camera to non-invasively identify pigments in single cells and map the spatial organization of phototrophic groups in complex microbial communities.

Resonon's hyperspectral imaging systems are used in food research and industry to identify defects, characterize product quality, and locate contaminants.

Examples of food analysis are:

Bruised Apples

A Resonon NIR-640 hyperspectral camera was used to scan apples, some of which were purposefully bruised pre-scanning. Resonon’s Spectronon software was used to classify the bruises. Peeling the skin shows the bruising, undetectable in the standard RGB image.

Nut Sorting

Hyperspectral imaging enables robotic sorting of nuts from shells and other foreign material, a job traditionally accomplished via manual sorting.

The image of walnuts shows the classification of the walnut meat (green) and shell (orange) components.

Hyperspectral machine vision detects small color differences more accurately and identifies different materials more reliably than conventional imaging. Resonon's system can be interfaced to robots, labeling devices, or used as feedback for sorting, grading, or process control.

Examples of machine vision are:


Hyperspectral infrared imagers can identify counterfeits, find defects, and eliminate prescription errors.

The image shows three types of white pills, indistinguishable by color to the human eye, but accurately classified via Resonon NIR-640 hyperspectral machine vision.

Machine Vision applications

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Airborne applications

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