Overview
In this workshop, students will take hyperspectral images and construct software and image processing tools that will expand the perceptible visual windows in humans. The subject of hyperspectral photography can be in pursuit of either artistic or scientific inquiries. Basic understanding of Python programming, image processing, convolutional neural networks, cloud computing and the physics of electromagnetic waves will be involved in the projects.
Learning objectives
- Learn fundamentals of hyperspectral imaging, some applications, and the physics of CCDs.
- Becoming familiar with light and how it interacts with matter, e.g. thermal radiation, reflection, absorption, and scattering.
- Defining a scientific or artistic objective and choosing a landscape to photograph with a hyperspectral camera to achieve these goals.
- Learning Python programming using libraries such as numpy, matplotlib, scikit-image, scipy, tensorflow, and keras with an introduction to matrices and linear algebra.
- Learn the basics of neural networks to work with images.
- Develop hyperspectral image processing algorithms and software that align with the science or artistic pursuits of the club.
- Learn to deploy computer processes into embedded devices such as a Raspberry Pi.
Prerequisites
Required
- Introductory Python knowledge:
Recommended Text
- Mathes, E. Python Crash Course: A Hands-On, Project-Based Introduction to Programming. No Starch Press, 2015.
- Raúl González Duque. Python para todos.
Others
- Familiarity with matrices, Numpy library in python, and photography.
- Basic knowledge on Raspberry Pi usage and programming.