Initial Publication Date: July 11, 2011

Part 2: Explore and Investigate Digital Images to Develop an Understanding of Their Properties2

Download a Greyscale and a Color Image

Download these two images of Lake Mead.

  1. Click the grayscale thumbnail image below to open a full-size version in a separate window. Then right-click (Win) or control-click (Mac) the full-size image to choose File > Save Image As... and save it to your Day 1 folder. Close the image window after you have downloaded its file.
  • Lake Mead 2004 grayscale small, with scale bar lake_mead_2004_grayscale.jpg
  • Then repeat the procedure for the color image of Lake Mead.
    • Lake Mead 2004 color small, with scale bar lake_mead_2004_color.jpg
  • Read this NASA Earth Observatory article to find out about the Lake Mead image .

  • Explore a Digital Image

    • Double-click the ImageJ icon ImageJ Icon Small to launch the application.
    • In ImageJ, choose File > Open..., navigate to your Day 1 folder, and open the lake_mead_2004_grayscale.jpg file. This is a grayscale satellite image of the area around Lake Mead, Nevada, taken by one of the Landsat satellites.
    • Zoom in and out



      • Using the Magnifying glass tool Magnifying Glass Tool , click once anywhere on the image. Keep clicking on the image, counting your clicks and watching how both the image and the image window title bar change as you zoom in.
      • What is the maximum magnification of the image, and how many clicks does it take to get there?

    1. The lake_mead_2004_grayscale.jpg image without magnification.

      lake_mead_grey_full

    2. The lake_mead_2004_grayscale.jpg image after four clicks of the magnifying glass tool or at 400% magnification.

      lake_mead_grey_zoom

    3. The lake_mead_2004_grayscale.jpg image at full magnification.

      lake_mead_grey_zoom_full

    Movie Icon
    The squares you see are the dots or pixels (short for picture elements) that make up the image. An important concept is that despite the impression given by those amazing FBI image processing techs you see in movies and television you can't zoom in to an image indefinitely. When you reach the point where you can distinguish the individual pixels, you won't see additional details by zooming in more.

    Scroll to move around

    When you're zoomed in, how do you move around an image?


    Investigate Pixel Data

    By the numbers - pixel values and coordinates

    A digital image no matter where it comes from or how it is produced is really just a string of numbers. Most of the time when you're working with digital images, the software keeps the numbers hidden from you. What makes ImageJ so useful is that you always have access to the numbers. Understanding this will help you and your students unlock the power of ImageJ.

    An important concept here is that storing all this information in an image file on your computer is much more efficient than it seems. The computer doesn't need to store x- and y-coordinates just the pixel values, in one long string, plus the width and height of the image. The coordinates are just information about the pixel under the cursor its column and row number that the software reports to the user.

    To reconstruct the image correctly, the computer just needs to "know" the number of columns and rows in the image. This kind of grid of rows and columns is also called a raster, which is why this type of digital image is also called a raster image and why ImageJ is called a raster image processor.


    Play With Color

    Lookup tables

    So far, you know that a digital image is a string of numbers arranged in rows and columns. How does the computer know what each number should look like when it displays that pixel on your screen? It's pretty simple, really. In addition to a string of numbers, the computer has a "secret decoder ring" called a Lookup Table that it uses in paint-by-number fashion. In a very simple image with only four possible values, the lookup table might look like 0 = black, 1 = blue, 2 = red, 3 = white. In an 8-bit image, the 256 possible values correspond to 256 colors. (Okay, we know what you're thinking, but black, white and all those grays ARE colors!) The lookup table can be stored in the file with the data, or you can control it using the software that's displaying the data.

    The key thing to remember about lookup tables is that they change the appearance of the image, not the pixel values themselves. The colors may change, but the numbers don't.
    Now we can put it all together into a simple definition of a digital image:

    A digital image is a series of numbers, arranged in a grid of rows and columns, and displayed according to a lookup table.

    This image is an 8-bit image. Each pixel is represented in the computer's memory by an 8-bit binary number, representing 256 possible values from 0 to 254. Another term for the number of binary bits used to describe the value of a pixel is bit depth. You can think of the bit depth as the 3rd dimension of an image (width and height are the other two).


    Color images


    When Values Represent Something Other Than Brightness

    Your Assignment: Zoom in on a Remote Sensed Image and Take a Screenshot

    1. Choose any remote sensed image. Open it using ImageJ and zoom in until you see the individual pixels.
    2. Use the Scroll tool Scroll Tool to hover over a pixel, reading its values and coordinates in the status bar.
    3. Write a brief description explaining what these numbers mean.
    4. Take a screenshot of the image while still zoomed in and showing the pixel you described.
    5. Then go to the Part 2: Share and Discuss page and post your image and description.

    Screenshot Instructions for Mac Users

    Screenshot Instructions for PC Users

    Source

    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.


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