Week 11: Using Satellite Data to Investigate Deforestation

Intro to Color Imaging: Capturing and Reproducing Color

All types of color imaging, including film, print media, and modern digital cameras, reproduce color by gathering brightness data from a scene through different colored filters. The scene is then reproduced on paper, film, or screen by using this information to control the amounts of different colors of dyes, ink, or light.

Primary colors

• In most cases, the filters used in color imaging are Red, Green, and Blue (RGB) — the so-called additive primary colors.
  Show me the additive primary colors
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• Color film has the filters built right into the film, with layers of light-sensitive emulsions recording the scene in Red, Green, and Blue light. The picture is then reproduced on photographic paper or transparency film containing layers of colored dyes. (The dyes used are Cyan, Magenta, and Yellow—the subtractive primary colors—the opposites of Red, Green, and Blue. In combinations, they produce all the colors we see. For example, Cyan and Magenta combine to make Blue.)
  Show me the subtractive primary colors
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• Modern inkjet printers produce colored pictures using tiny dots of cyan, magenta, and yellow ink, with black ink added to produce deeper blacks and better contrast. This combination of inks is called CMYK.
  
  
  
  
• Offset printing presses, used to print magazines, newspapers, catalogs, posters, and similar items also produce colored pictures using a CMYK process, layering inks in patterns of small dots of cyan, magenta, yellow, and black ink.
  
  
  
  
• If you look at your computer monitor with a magnifying glass, you will see that each pixel on the screen is made up of a set of red, green, and blue bars or dots.
  
  
  
  
  
• The sensors in digital cameras have the red, green, and blue filters coated right on the surface of each light detector cell in an alternating pattern called a Bayer Pattern.
  Summary: Light-based (emitted) color uses the additive primary colors red, green, and blue. Print-based (reflected or transmitted) color uses the subtractive primary colors cyan, magenta, and yellow.

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Multispectral and hyperspectral imaging

• Scientific satellites often carry multispectral instruments that produce images in different wavelength bands. On LANDSAT satellites, the Multispectral Scanner (MSS) instrument records 4 bands and the Thematic Mapper (TM and ETM+) instruments record 7 and 8 bands, respectively, including visible and infrared wavelengths.
  
  
  
  
• Newer instruments carried by satellites or aircraft can record images with hundreds of bands. This technology is called hyperspectral imaging. Examples are NASA/JPL's AVIRIS instrument (224 channels) and NASA/Goddard's EO-1/Hyperion instrument (220 channels).

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Deconstruct a Color Image

ImageJ has the ability to separate a color image into its component bands, or channels.

Download a color image

1. Click the image below to open a window containing a full size version.
2. Right-click (Win) or control-click (Mac) on the larger image and download the image file to your Week 11 folder.
   
   
   
   

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Launch ImageJ and open the image

1. Launch ImageJ , choose File > Open, navigate to the Week 11 folder, and open the deforestation image you downloaded.
2. Look at the image window status bar. What type of image is this, and how much memory does it occupy?
   Show me the answer
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   This is a 24-bit RGB (Red,Green,Blue) image, and it occupies 5.9MB of memory.
   
   
   

Show me the number of possible colors in a 48-bit color system
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A 48-bit color system can represent 65536 x 65536 x 65536 = over 281 TRILLION colors!


1. Mouse around the image and look at specific pixel values in the ImageJ window status bar.
   Show me where to read pixel values and coordinates
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2. Recall from earlier in the course that the three values represent a color recipe for the pixel—so many units of red light plus so many units of green light plus so many units of blue light. Your computer uses these numbers to control the brightness of the colored dots on your monitor at each location. (This applies to EVERYTHING you see on your computer - NOT just the digital images in ImageJ.)

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Separate the color channels

1. Choose a specific pixel—zoom in on the image if you want.
2. Write down the pixel's coordinates (X,Y) and color values (R,G,B).
3. Choose Image > Color > Split Channels. Your RGB color image separates into three grayscale images, in three different windows.
4. Note the (red), (green), and (blue) added to the image window title bars.
   Show me where to look
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Inspect the RGB pixel values

1. Activate the red channel image (from the bottom of the Window menu), go to the pixel with the XY coordinates you wrote down (pan and zoom if necessary) and examine the pixel value (now a single number). How does this value compare to the Red value you wrote down for the pixel at the same coordinates in the RGB image?
   Show me the answer and an example
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   The pixel value from the red channel image should be the same as the first number—the red value from the RGB image at the same coordinates.
   
   
   
   
   
   
   
2. Predict the pixel values at the same coordinates in the green and blue channel images, then examine the images to check your predictions.
   Show me the answer
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   The pixel values from the green and blue channel images should be the same as the G and B values at the same pixel location in the RGB image.
   
   
   
   
   

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Reconstruct a Color Image

ImageJ can also construct or reconstruct an RGB color image from the individual red, green, and blue channel images.

1. Choose Image > Color > Merge Channels...
2. Assign the red image to the red channel, the green image to the green channel, and the blue image to the blue channel. Nothing should be assigned to the Gray channel.
3. Uncheck the Create Composite option and check the Keep Source Images option.
4. Click OK. The resulting image should look exactly like the one you started with in this activity.

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Optional (if you have time) - Make a False Color Image

This is cool and all, but why in the world would you want to deconstruct a color image? Here are a couple of ideas...

Make a false color image

What happens when you assign the images to the wrong channels?

1. Close the reconstructed RGB color image you created in the previous section. The three grayscale color channel images should still be open—if not, you'll have to open the RGB image and split the channels again.
2. Choose Image > Color > Merge Channels...
3. Assign different images to the red, green, and blue channels and create a new RGB image.
Show me an example
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Image reconstructed as blue, red, green.








4. Try assigning the SAME image to all three channels. Predict what you think it will look like, then test your prediction.
Show me the answer
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If you assign the same grayscale image to all three color channels, you will get a 24-bit grayscale image.

False color images are used to make specific features stand out so they are easier to see or interpret.

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Pump up the contrast

Due to atmospheric haze, most images shot from the International Space Station have poor contrast and flat colors. What can we do in ImageJ to punch up the contrast? The idea is to split the channels, manipulate them separately, and then merge the channels back together.

1. Close any RGB images that are open. You should still have the red, green, and blue channel images open. (If not, you know what to do!)
2. For each of the three channel images:
   • Choose Image > Adjust > Brightness / Contrast.
   • Click the Auto button in the B&C window (or adjust the Minimum and Maximum sliders by hand)
   • Click the Apply button.
     Show me the Brightness and Contrast window
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3. Choose Image > Color > Merge Channels...
4. Assign the appropriate images to the red, green, and blue channels and click OK.
   Show me the result
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   Compare this result to what you get when you auto-enhance the contrast of the original 24-bit RGB color image.
   
   
   
   
   

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Resources

• Color Models
• How Color Film Works
• Digital Cameras and Bayer Patterns
• Color film
• AVIRIS
• NASA Earth Observatory - Tierras Bajas Deforestation