Hyperspectral Imaging Applications Across Research and Industry
Explore hyperspectral solutions and case studies
Applications
Hyperspectral imaging technology enables researchers and engineers to identify materials, measure chemical composition, and analyze objects beyond what is visible to the human eye. Using advanced hyperspectral cameras, SWIR cameras, and hyperspectral imaging systems, these solutions support a wide range of hyperspectral imaging applications across agriculture, mining, environmental monitoring, food inspection, defense, and scientific research.
Resonon hyperspectral 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 applications and case studies 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.
A common application of hyperspectral imaging in agriculture is the early detection of crop stress. By analyzing how plants reflect light across many wavelengths, the systems can identify nutrient deficiencies, water shortages, weeds, and diseases before they are visible to the human eye.
Explore real examples of hyperspectral imaging in agriculture:
Application Example
Detecting Broadleaf Weeds in Rice Fields with 99% Accuracy
An Airborne Pika L system detected and classified three different broadleaf weed species in rice fields as early as 15 days after sowing with over 99% accuracy across all growth stages.
Hyperspectral Imaging to Estimate Strawberry Macronutrients
A Pika XC2 imager was used to scan strawberry leaves, flowers, and fruit to predict macronutrient concentrations. Predictions of nitrogen, phosphorous, potassium, and calcium concentrations had R2 > 0.64.
A Resonon Pika II (predecessor to the Pika L) hyperspectral airborne system sampled 960 wheat plots with varying levels of stem rust disease, achieving an overall 88% disease classification accuracy.
A Pika L hyperspectral imaging system was successfully used to identify citrus canker in the lab and verified via UAV scans in the orchard, with between 94% and 100% accuracy in distinguishing healthy and infected trees.
A team at the University of Littoral Côte d’Opale integrated a Resonon Pika IR with an unmanned-aquatic drone to autonomously find and identify plastic waste in coastal environments.
Resonon systems have been used for many biological and medical applications.
Application Example
Hyperspectral Exploration of Bird Plumage Coloration
A Resonon Pika UV was used by researchers to analyze plumage coloration patterns in a rare hybrid bird-of-paradise compared to its parent species using the 325-700 nm wavelength range. The ultraviolet wavelengths are an important component of some animal visual systems.
A Resonon Pika XC2 benchtop reflectance system was used to acquire reflectance data of the hands of 100 human subjects of different skin tones, after which, classification algorithms were used to find veins in HSI images.
Resonon's Bio-LIF
(Laser Induced Fluorescence) system is being used by researchers to
significantly reduce the time to develop new mutations of red fluorescent
proteins (fluorophores) used in diagnostics, life science research, and new drug discovery.
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.
Scientists from NIST and The Ohio State University used a Resonon Pika II (predecessor to the Pika L) hyperspectral imaging camera to characterize wounds.
Resonon hyperspectral imaging cameras are used in air, space, and underwater vehicles to capture detailed spectral data for a wide range of applications.
Application Example
NASA ARCSTONE
Resonon partnered with NASA to design and build the ARCSTONE hyperspectral instrument to calibrate lunar reflectance in order to increase understanding of Earth systems (i.e., weather, climate change) while reducing future imaging satellite costs. Launch is scheduled for Q2 2025.
Airborne Identification of Archaeological Artifacts
A Resonon Pika IR+airborne hyperspectral imaging system was used to locate and classify various archaeological artifact samples spread across a grass and sand/silt survey region.
A Resonon Airborne Pika L system was used to help predict yield in wheat as a function of fertilizer concentration. LAI and chlorophyll were measured for 24 plots using 8 nitrogen treatments.
Using Hyperspectral Imaging to Identify Invasive Weeds
In Montana, leafy spurge is estimated to impact the state’s economy by $18 million per year. A group of researchers at Montana State University used a Resonon hyperspectral camera to identify leafy spurge with 95% accuracy.
Resonon's hyperspectral imaging systems are used in food research and industry to identify defects, characterize product quality, and locate contaminants.
Application Example
Potato Chip Oil Content
A group at Virginia Tech used a Pika IR+ to rapidly quantify oil content and oil distribution in commercial potato chips with high accuracy.
A Pika XC2 hyperspectral imager was used to non-destructively assess moisture in macadamia nuts. High prediction accuracy (R2 ≥ 0.93) was achieved for both kernels and nuts-in-shell using either human or computer-generated regions of interest.
A Resonon Pika XC2 was used along with a Convolutional Neural Network (CNN) to predict the number of days until ripeness of avocados with an error of 1.2 days.
A Resonon Pika XC (predecessor to the Pika XC2) was used to predict marbling in beef steaks. The model predictions were highly-correlated with human judges trained in the Japanese Beef Marbling Standard.
A Pika IR+ 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 a standard RGB image.
Application Example
Cooked Food
Subtle color changes associated with food quality can readily be identified using hyperspectral imaging.
The image of chicken nuggets shows the classification: missing breading (red), crispy (green), and appropriately-cooked (blue).
Industrial Applications
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.
Application Example
Automated Solder Quality Inspection
A Pika L hyperspectral camera was used to develop an automated system for assessing solder quality on circuit boards.
The system can evaluate solder quality, detect defects, and ensure uniformity.
A major manufacturer of laminates uses Resonon machine vision systems at multiple facilities to identify over 30,000 products daily from a library of several thousand.
The image shows two nearly-identical products that are accurately differentiated using Resonon machine vision.
Application Example
Pharmaceuticals
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's Pika IR+ hyperspectral machine vision.
