Initial Publication Date: July 18, 2011

Day 1—Get to Know Your Digital Image

Nile_bend

Before you begin analyzing anything, whether it's a flower, a bouncing ball, a digital image, a person, or a distant galaxy, you need to spend time getting to know as much about that thing as possible. To guide your analysis, you need to establish what you do and don't know about the thing or phenomenon and its underlying form and function. Otherwise, your lack of understanding may cause you to ask the wrong questions, make the wrong observations, and ultimately arrive at the wrong results and conclusions. You may also unknowingly change the thing itself in the process of your analysis.

The overall goal of today's material is to help you develop strategies, insights, and practical tools for understanding the nature of digital images and the objects and ideas they represent. You may be tempted to skip over tasks that seem tedious, but please don't—everything you do has a purpose.

Today's material will be a mixture of review of what you have already learned, combined with deeper insights into that material, along with a generous helping of practical tips to make you—and your students' lives easier.


Day 1 Goals

  • Review techniques for opening images in ImageJ and learn some new ones.
  • Review the basic characteristics and properties of digital images.
  • Examine and compare different types of images.
  • Understand the differences between image file formats.
  • Convert between images of different data types.
  • Understand the practical difference between computer memory and file storage.
  • Review stack terminology, control, uses, and operations.

Day 1 Tasks

  1. Use a variety of methods to open digital images in ImageJ,
  2. Compare and contrast digital images that vary by dimension, bit depth, and file type.
  3. Locate a digital image and describe its characteristics in terms of bit depth and pixel histogram distribution.
  4. Stack digital images and apply stack operations.
  5. Engage in an online conversation with your colleagues around the use of "stacked data" in your teaching.

Sources

1Adapted from Earth Exploration Toolbook chapter instructions under Creative Commons license Attribution-NonCommercial-ShareAlike 1.0.
2Adapted from Eyes in the Sky II online course materials, Copyright 2010, TERC. All rights reserved.
3New material developed for Earth Analysis Techniques, Copyright 2011, TERC. All rights reserved
4From Remote Sensing Math: A Brief Mathematical Guide by Dr. Sten Odenwald, NASA 2011.