Earth Analysis Techniques > Image Analysis Modules > Introduction to Image Analysis > Day 1—Use Images to Analyze Earth > Part 2: Explore and Investigate Digital Images to Develop an Understanding of Their Properties

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

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.
2. Then repeat the procedure for the color image of Lake Mead.

## Explore a Digital Image

• Double-click the ImageJ icon 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 , 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?
• It takes 10 clicks to reach the maximum magnification of 32x (3200%).

1. The lake_mead_2004_grayscale.jpg image without magnification.

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

3. The lake_mead_2004_grayscale.jpg image at full magnification.

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.
• To zoom out, hold down the Alt (Win) or Option (Mac) key while you click on the image with the Magnifying glass tool . You can keep zooming out beyond 100%, all the way down to about 3%. This may be useful when you are working with very large images and you need to see the entire image on screen at one time.
• To quickly return to 100% from any magnification, double-click the Magnifying glass tool on the toolbar.

### Scroll to move around

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

• Zoom in to about 800% magnification.
• Use the Scroll tool to drag the image in the window in any direction. Because it's often useful to scroll the image while you're using other tools, you can bring up the scroll tool at any time by pressing the space bar. Try it now select a different tool, move your cursor back over the image, hold down the space bar, and drag the image around in the window.

## 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.
• Zoom in until you can easily see the individual pixels.
• Move your cursor around the image and watch the numbers on the ImageJ status bar (just below the toolbar in the ImageJ window). The x and y values represent the x (horizontal) and y (vertical) coordinates. In math class, the origin (0,0) is usually in the lower left corner of a graph. Where is the origin coordinates (0,0) of a digital image?
• The image origin (0,0) is in the upper left corner.

• To the right of the x and y coordinates on the status bar, it says value = and a number. Move your cursor around the image some more and see if you can tell what the value represents.
• Zoom back out to 100% and move your cursor over a dark region of the image, then over a light region, watching the value change.
• In this image, the value represents the brightness measured by the detector on the satellite at that particular location. In general, though, pixel values can represent anything that can be expressed as a number and organized in rows and columns.
• Mentally fill in the blanks of this statement with appropriate words: "In this image, light pixels have ______ values and dark pixels have ______ values."
• In this image, light pixels have higher values and dark pixels have lower values.
• What's the lowest pixel value you can find in the image? What's the highest?
• Obviously, your answers will vary depending on which pixels you looked at. As it turns out, the lowest pixel value in the image is 0 (black) and the highest is 255 (white). This gives a range of 256 possible values - although there's no guarantee that a particular image will contain any pixels of a particular value.
• The number 256 is significant, because it represents the number of possible values of an 8-bit binary number (from 00000000 to 11111111).
• Fortunately, you don't have to worry about binary numbers, but computers use them for all their number crunching and math wizardry. All you need to know is that when an image is described as an "8-bit" image, its pixels can have any of 256 possible values.

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

• Navigate to your Week 2 folder and open the lake_mead_2004_color.jpg file. This is a color version of the image you have been working with.
• Briefly explore the image by zooming, scrolling, and looking at coordinates and pixel values. Do you notice anything different about those pixel values?
• Yes, in this color image there are 3 values (numbers) for each pixel. These represent three separate color channels Red, Green, and Blue (RGB). Think of the three numbers as a recipe. Each value represents the amount of its corresponding color. In other words, a pixel with color values of 192,125,75 has 192 parts of red light, 125 units of green light, and 76 units of blue light (out of a maximum 255 parts) - giving that pixel a brownish orange color.

RGB color images like this don't need lookup tables, because each pixel in the image has a recipe for how it should look. However, since each pixel now requires three 8-bit numbers rather than just one, this image requires three times the computer memory as the grayscale image.

• Close the color image.

## When Values Represent Something Other Than Brightness

• Lake Mead DEM (8-bit) (TIFF 1.4MB Jan30 10)
• This image is a Digital Elevation Model (DEM) of the Lake Mead area. Instead of the brightness, each pixel value in the image represents the elevation at that location. The image has been calibrated so that the pixel values from 0 to 255 are converted to elevation (in meters). Mouse around the image and look at the pixel (elevation) values.
• Can you find the elevation of the lake itself?
• The elevation of the lake is about 325 meters above sea level. The calibrated value is shown on the ImageJ status bar, followed by the original 8-bit value in parentheses.

• Apply different lookup tables to the image (Image > Lookup Tables).
• This is how it looks with the 32_Colors lookup table.

• Use Analyze > Surface Plot to re-create a 3-D view of the scene. Choose Analyze > Surface Plot. Check Draw Wireframe, Shade, Draw Axis, and Smooth in the Surface Plotter dialog box.
• Use one of the line selection tools to select a path through the scene. Then choose Analyze > Plot Profile to create a profile plot along the path.

## 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 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

• Press Command-Shift-4 (Command key = Apple key) all at the same time and drag a box over the area of the screen that you want to capture. Depending upon your operating system, this will produce a file named Picture1.png or Screen shot Date Time.png on your desktop. Move the screenshot to your Day 1 folder or to a place where you can easily find it. Double click on the file to open it in Preview. Rename the image and save it as a jpeg, giving it a name that describes it, such as Lake_Mead_pixel_zoom.jpg.

### Screenshot Instructions for PC Users

• Press Alt and Printscreen at the same time. This will save an image of the screen to the computer's clipboard.
• Launch Paint and choose Edit > Paste.
• Save the image as a jpeg, giving it a name that describes it, such as Lake_Mead_pixel_zoom.jpg.