Hyperspectral and Multispectral Imaging (HSI & MSI) Training Boot Camp by Tonex
Target Audience: Researchers, engineers, and professionals working in remote sensing, healthcare, agriculture, material science, and other imaging-related fields.
Day 1: Foundations of HSI & MSI
Morning Session: Introduction and Fundamentals
- Overview of Imaging Technologies
- What are Hyperspectral Imaging (HSI) and Multispectral Imaging (MSI)?
- Key differences between HSI and MSI.
- Applications in different fields (agriculture, defense, healthcare, etc.).
- Basic Principles
- Spectral resolution, spatial resolution, and temporal resolution.
- Understanding electromagnetic spectrum and reflectance.
Activity: Hands-on demo with spectral data and image samples. Explore spectral bands with software tools.
Midday Session: Equipment and Data Acquisition
- Hardware Basics
- HSI cameras: pushbroom, snapshot, and whiskbroom.
- MSI sensors and platforms (e.g., satellites, drones, handheld devices).
- Data Acquisition Techniques
- Calibration of HSI/MSI systems.
- Factors affecting data quality (lighting, motion, environment).
- Real-time data capture in lab or field conditions.
Activity: Live demo of data acquisition using HSI and MSI cameras.
Afternoon Session: Data Processing and Visualization
- Preprocessing Steps
- Radiometric, geometric, and spectral corrections.
- Noise reduction techniques.
- Visualization
- Spectral plots and band selection.
- Pseudocolor images for feature representation.
Activity: Perform preprocessing and visualization tasks using HSI/MSI datasets in software like ENVI, MATLAB, or Python.
Day 2: Advanced Techniques and Applications
Morning Session: Analysis and Machine Learning
- Spectral Analysis
- Feature extraction and dimensionality reduction (e.g., PCA, ICA).
- Classification techniques (e.g., k-NN, SVM, neural networks).
- Spectral unmixing and endmember detection.
- Machine Learning Integration
- Deep learning for image segmentation and object detection.
- Application of convolutional neural networks (CNNs) in HSI/MSI.
Activity: Apply machine learning algorithms to classify spectral data in a given dataset.
Midday Session: Industry Applications
- Agriculture
- Crop health monitoring and precision farming.
- Healthcare
- Medical imaging and diagnostics.
- Defense and Security
- Target detection and surveillance.
- Environmental Monitoring
- Pollution analysis and land cover classification.
Activity: Solve a real-world problem in one application area using HSI/MSI data.
Afternoon Session: Future Trends and Project Work
- Emerging Technologies
- Advances in hyperspectral and multispectral hardware.
- Integration with IoT, AI, and cloud platforms.
- Capstone Project
- Work in teams to analyze a complete HSI/MSI dataset from acquisition to visualization.
- Present findings and insights.
Activity: Teams present their project work and receive feedback from instructors.
Resources provided:
- Lecture slides and technical documentation.
- References to online tutorials and further reading materials.
Outcome: By the end of the boot camp, participants will be proficient in the principles of HSI/MSI, understand their practical applications, and gain hands-on experience in data acquisition, processing, and analysis.