Part 2K: Making the Connection

This part helps make the connection between the Afterglow Access tools and the matrices we have been exploring.

(Leaders/Teachers:refer to the help sheet for Section 2, Parts K-R)

Section 2: Parts H-J Notes and Journal answers

Open Afterglow Access if you do not already have it open.

Link to Afterglow Access

If you do not have a file (image) open, please choose one. You should be on the Workbench with the Display Settings visible on the right. Let’s examine what is here.


1. The Display Settings panel lists Brightness and Contrast Settings under the histogram. Note: there are several icons at the top right of the histogram graph that allow zooming etc.

a) Examine an image of Jupiter – find this in your file library folder. Open the Sample folder, then IDATA folder, then scroll down to Jupiter. After checking the box, click on the open button. It should automatically open in the viewport window.

  • Use the ‘Zoom To Fit’ button towards the right, below the image.
  • Now try the ‘Brightness and Contrast Settings’ under the histogram. They are labeled: Faint Target, Default, and Bright Target. Try each, paying attention to the image AND the histogram graph.

b) A little further down the page drop down menus for Background Level Percentile and Saturation Level Percentile. Record the numbers seen when you click the Faint Target, the Bright Target, and Default in turn. Then change the numbers to anything you would like. Does it also change the graph? (Pay attention to the red vertical, dotted lines).

c) Next, use the Sonifier tool to see if you can hear any changes you made to the Brightness and Contrast Settings. Try sonifying small parts of the image by using the Custom region settings to test this.

d) Go back to the histogram. Let’s examine the meaning of the red vertical lines and how they relate to the Background and Saturation Level Percentiles. Josh, the software engineer, helps in explaining:

“The telescope we use has a “16 bit” camera. This means the information stored in each pixel can have 2^16 = 65,536 different values – in this case, “counts”, or brightness values. The counting of the values starts at zero and goes to 65,535. That gives 65,536 values.” (It is similar to why 0 to 9 is ten numbers.)

“Computer screens can only display values for red, green, and blue which range from 0 to 255 (8-bit integers=2^8). We need to convert the CCD pixel values of the 16 bit camera (which gives 16-bit integers) to 8-bit Red, Green, Blue, (RGB) integers. We do this by choosing a pixel value in the CCD image which we will set to black (RGB = 0,0,0) and then choosing a pixel value in the CCD image which we set to white (255,255,255).”

How do we choose where the black and white pixel is? Read on!

This is where the percentiles for background level and saturation level comes in. The algorithm actually uses the histogram for this. The values on the x-axis are the pixel values recorded by the camera (anywhere from 0 to 65,535), and the value on the y-axis is the number of pixels with that value. The curve plotted is used to set the “black” and “white” values, as explained next:

“If you march along the curve starting from the far left, the red vertical line is set at the point where 10% of pixel values are to the left. Those are then made black, thus, the Background Level Percentile is 10% (Default). Continue to march along the curve. When the point where 99% of pixel values are to the left, the Saturation Level Percentile is 99% (Default). Then all pixels to the right of that are made white.”

  • Every value in between is a shade of gray. Again, these two values are the defaults, and can be returned to by clicking the Default Preset above the graph.
  • These default values also can change by using the presets for Faint Target and Bright Target, or by you typing in your own percentile.
  • Play with the settings to see how it affects the image of Jupiter. Pay attention to the red vertical lines on the histogram.

One other note: This problem with the computer only displaying 255 values is the reason why astronomers deal with data rather than images. See if you can remember the difference between the number of pixels in 16 bit cameras and 8 bit computer screens.

In this 4:15 video, Chris relates music to background level and noise:


2. ACTIVITY for Background level:

Recall that light waves and radio waves are part of the electromagnetic spectrum, and hence, share a lot of the same properties.

If a transistor radio is available, experiment to find “background levels” for radio “light” instead of visible light. A transistor allows radio waves to be heard as sound waves.

You will need to turn the tuning button down to low numbers on the AM band to here this background sound.

Record your answers in your journal.

  • a) What do you think is causing the background radio sound?
  • b) What do you think is causing the background light found on an astronomical image?
  • c.) Thought experiment: What if you took the radio to a place where there was no interference? Do you think you would still hear some crackles or buzz?

***Note: The internal electronics of the radio (and camera for light) also produce interference. This is called “noise”, which is different from the external background levels.

3. Return to Afterglow Access (AgA), and look again at the histogram graph and the saturation level settings. Answer the questions below in your journal.

  • d) Which of these, the background level or saturation level, correspond to a large number of pixels with a small number of counts (or values)?
  • e) Which of these, the background level or saturation level, correspond to a small number of pixels with large counts (values)?



The idea of “counts” has been discussed several times in this Module. Recall it is the value recorded in each pixel.

1. What does the value in each pixel tell an astronomer?

2. Examine an image of your choosing in Afterglow Access. Record your answers in your journal.

  • f) Where are the counts (pixel values) displayed in AgA? (Hint: It is not labeled, and there are at least two places) Record your answer in the JOURNAL.
  • g) What corresponds to counts on the CCD poster used earlier?



The Color Map setting has a drop down menu from which you can choose an “intensity” maps. Different brightness levels (same as pixel values or counts) are assigned different colors.

It has nothing to do with the color of the photon striking the CCD camera.

Mathematical algorithms are used to map different intensities levels to different colors.

The algorithm basically assigns colors instead of shades of gray to the 0-255 values used by the computer to display what is in each pixel.

Answer the following questions in the JOURNAL BOX below.

1. Recall the CCD poster activity at the very beginning of this Exploration. Why did we have four posters? .

2. What filter we have been using for ithe code for an image request?

  • a) If your images were not taken with a color filter, how could AgA display color images?
  • b) Play with the Color Map settings and the image you have in the viewer panel. Record your favorite Color Map setting.