Data Formats, Contrast Stretching,
and Density Slicing

Part I. Data Formats and Import/Export

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Begin by copying the murrells-inlet_cams_1997-08-02.lan file to your local hard drive.  After you begin IMAGINE, find and select the Import button on the main icon panel.

When the Import/Export dialog box appears, do the following:

• Make sure the [Import] option is selected.
• Specify Type as [LAN (Erdas 7.x)].
• Specify Media as [File].
• Now select murrells-inlet_cams_1997-08-02.lan as the input file.
• After you have specified the Input File (*.lan), a filename with the same prefix but with an IMAGINE (*.img) extension should automatically appear in the Output File (*.img) column. Make sure the file is going to be written to the correct directory, select [OK] and wait for another window to appear. We will not be modifying the image during the import process but, there are some options menus that you may wish to look at, especially the Import Options (where you can layer stack selected individual bands).
• When you are ready to import the image, select [OK]. When the import job has completed, select [OK] from the job state window.

Now display the newly imported murrells-inlet_cams_1997-08-02.img file in the viewer with RGB = 6,4,2. This equates to placing the NIR band (6) in the red image plane, the red band (4) in the green image plane, and the green band (2) in the blue image plane.
 

1) Briefly describe (you may want to use simple illustrations) the logic and differences between the four common generic binary data storage formats and any advantages/disadvantages of each including:
 
a) band sequential (BSQ)
b) band interleaved by line (BIL)
c) band interleaved by pixel (BIP)
d) run-length encoding

Part II. Contrast Stretching and Histogram Equalization

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Image

File Name	murrells-inlet_cams_1997-08-02.img	Quick View
Location	Murrells Inlet, SC	Altitude 1,524 m AGL
Sensor	Calibrated Airborne Multispectral Scanner (CAMS)
Spatial	3 ?3 m
Temporal	August 2, 1997
Spectral	Band 1 = Blue (.45-.52) Band 2 = Green (.52-.60) Band 3 = Red (.60-.63) Band 4 = Red (.63-.69) Band 5 = NIR (.69-.76) Band 6 = NIR (.76-.90) Band 7 = NIR (1.55-1.75) Band 8 = MIR (2.08-2.35) Band 9 = Thermal (10.5-12.5)

Display murrells-inlet_cams_1997-08-02.img in an imagine viewer with the following CIR band selection: band 6 in the red plane, band 4 in the green plane, and band 2 in the blue plane (RGB = 6,4,2). Once the image is displayed in the viewer, open the ImageInfo dialog. As you discovered in the previous exercise, the ImageInfo window displays band, statistics, and map information for the selected channel as well as projection (including elevation) infomation if the image has been rectified and projected. The band (layer) you choose to view can be modified so that you can in turn view each band individually. Since this image has not been rectified or projected, the Map Info is in file coordinates, not map coordinates (i.e. UTM coordinates) and the Projection Info is blank.

Find and select the button that displays the layer Histogram. The range of the x-axis consists of brightness values from 0 to 255 (corresponding to 8-bits; refresher: 0 is black and 255 is bright white). The y-axis starts at 0 and increases upwards, showing the total number of pixels that are being placed into each x-axis range from 0 to 255. You can query the histogram by moving the cursor into the window displaying the histogram. Roam around inside the graph and notice that the cursor arrow becomes a cross. The x- and y-axis values are displayed for the center cross location within the histogram. The red line down the middle represents the mean value of the histogram. Resize the histogram window by dragging the corners for a closer inspection of the data distribution. Note that changing the layer in the ImageInfo dialog will change the histogram as well.
 

murrells-inlet_cams_1997-08-02.img histogram of band 7

2) On a sheet of paper, recreate each of the histograms for all nine bands and briefly interpret the general characteristics of each band's histogram based on your knowledge of the electromagnetic spectrum. Label the highest frequency represented, minimum, maximum, and the mean value for each band.

Now close the ImageInfo window and leave the CIR image displayed in the Viewer.  Select the [Raster | Contrast | Brightness/Contrast] menu item.  A menu will appear with sliding bars that allow you to change the brightness (symbol that looks like the sun) and the contrast (symbol that looks like a circle half shaded) of the image. Click the [Apply] button in this menu to view the contrast changes applied in the viewer. Experiment using this tool by increasing the contrast of the image to a level where the estuaries and wetlands within Murrell's Inlet can be identified.
 

3a) Why do you think the contrast between the uplands and the wetlands is so great?

3b) What contrast levels did you choose to view the estuaries and wetlands within Murrell's Inlet?

When you are done experimenting with the contrast tool, select [Reset] then [Apply] and close the window.  Do NOT save any contrast changes you made to the image. After the image has been redisplayed in the default contrast settings, go to the [Raster | Contrast | General Contrast] menu item.  When the Contrast Adjust tool appears, click on the [Breakpts...] button. This brings up the Breakpoint Editor and three histograms (one for each band displayed in the image) should appear. Each histogram corresponds with the color memory plane in which the individual bands are being displayed (Red, Green, Blue). Notice the light gray histogram that is behind each colored histogram (you may need to increase the size of the Breakpoint Editor to see this clearly). These light gray histograms correspond to the input file's raw data values that you saw earlier in this exercise. The change between these two histograms (light gray and colored) represents the contrast enhancements that have automatically been performed to the image by the software. The enhancement represented graphically by the colored histograms is a contrast stretch over 2 standard deviations from the mean data value in each band.
 

4a) On a new sheet of paper, draw and label in the same way as before the newly contrast stretched histograms for bands 6 (histogram in the red plane) and 4 (histogram in the green plane) .

Each sloped line that crosses a histogram illustrates the transformation of image data values into brightness values and is a graph of the lookup table. The line shows how the input file value of x is changed to produce an output brightness value of y. By moving the cursor into the windows and over the histograms the cursor changes again into a cross and information about the histograms can be gained. The buttons along the top of the Breakpoint Editor allow you to manipulate these line transformations in different ways. Now go back to the Contrast Adjust window and make sure the Method is set to [Histogram Equalization] and then click [Apply]. Notice the changes that occur in the Breakpoint Editor to all three histogram patterns and in the slopes of their lines. Now click the [Apply All] button in the Breakpoint Editor. You may want to zoom in on selected areas to get a better feel on what the contrast enhancements are doing to the displayed image.
 

4b) What happens to the histograms when using histogram equalization? How does it affect the image? When would histogram equalization not be appropriate to use?

Now move the cursor into each histogram window and when over the graph select the right mouse button, this should display a hidden function window. In this hidden window find and select [Undo All Edits] for each of the three histograms and then click [Apply All] in the Breakpoint Editor. This will return the histogram to it original condition. Now go to the Contrast Adjust window where you selected histogram equalization before and this time change that selection to [Standard Deviations].  Notice that the default standard deviation setting to view images is 2.0. Move down to the single box just below this selection and change the number of the standard deviations to 4.0 and then select [Apply] in that window and then [Apply All] in the Breakpoint Editor. Notice the changes that occur in both the image and in the histograms.
 

5a) What happens to the image when the Standard Deviation is changed to 4.0? Why?

Now change the number for the standard deviations to 1.0 and select [Apply] in both menu windows.
 

5b) What happens to the image when the Standard Deviation is changed to 1.0? Why?

Part III. Density Slicing

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Par Pond, South Carolina

Raw TM Data Band 3	5 Class Density Slice

Close all contrast tools and go to [File | Clear] (you don't need to save any changes). Now open the marco-island_spot_1988-10-21.img file you used in last week's exercise as a [Pseudo Color] image using the NIR channel (band 3). You are going to density-slice the image into three general land cover classes:

1. Water
2. Vegetation
3. Urban/Barren

To do this you will need to select the [Raster | Attributes...].  Also, bring up the raw data value histogram for band 1 to aid in your feature discrimination. This can be done using the same procedures discussed in Part I.

Once you have both a histogram and a Raster Attribute Editor open you are ready to proceed. Examine the row and columns in the Raster Attribute Editor. The rows in the table correspond to the input file data values that can range from 0 to 255 (8 bits). The columns show a histogram frequency and a color for each brightness value, as well as a binary opacity (on / off) setting.  As you scroll through the Raster Attribute Editor you should see a progression from dark to light in color. You can resize this table to display more or less of the columns and rows as you wish.

Move the cursor back into the Viewer where the NIR band is displayed and with the right mouse button bring up a Quick View menu and select [Inquire Cursor].  Roam the cursor around the image and watch to see what typical brightness values (pixel values) are associated with the water class, the vegetation class, and the urban/bare land class within the NIR band. You should be trying to get an idea about what boundary values correspond with each of these classes (i.e. vegetation = 80 to 255, water = 40 to 79, urban/bare land 1 to 39.  NOTE: these are wrong choices and are only given for example. At this point you may wish to consult the histogram of the NIR band to make any further estimates as to the class into which you plan to place a particular brightness value.

After you have used the Inquire Cursor and determined the boundary values for the three classes listed above, move back to the Raster Attribute Editor. What you will now do is to assign to each of these three classes characteristic colors that will represent them in the image (i.e. instead of water being dark black in the NIR band it will appear as the color you chose- blue might be nice). The method for assigning your characteristic colors is quite simple. Use the left mouse button to select ("highlight") each row you feel is characteristic of one particular class, i.e. water. This can be done by clicking on each row number (farthest left column) individually or by selecting a series of rows. To select a series you should depress the left mouse button, and while keeping it depressed, move the mouse up or down within the row column. This will have the effect of scrolling the attribute editor up or down, highlighting all the rows along the way. If you wish to do a combination of scrolling and selecting individually then make sure you hold the shift key down anytime you depress the left mouse button and proceed as before.

Once you have made your row selections you can modify the color in all of them by depressing the right mouse button when the cursor is over the color column.  Note that the color will only change in the rows you have selected.  You have the option of choosing a canned color or using [Other...] to create your own color. If you choose [Other...] the Color Chooser will open and you have two options to choose from: [Standard] or [Custom]. The [Standard] gives you the ability to choose colors by name. The [Custom] option allows you to choose a color using the three sliding bars in RGB (Red, Green, Blue) mode or IHS (Intensity, Hue, Saturation) mode. You can also pick a color by using the cursor to move the black circle within the color wheel. You will no doubt end up using some combination of all the above.  Whatever process you choose to pick a color, select [Apply] and the color should appear on the IMAGINE Viewer representing that "slice" or class of the NIR band. Repeat this step for all three classes.
 

5) Record the range of values you used to density slice each land cover class:
 

1. Water =
2. Vegetation =
3. Urban/Bare land =

Now save this new density-sliced image into your a temporary folder using [File | Save | Top Layer As].

Now export the NIR band into a GIS (*.gis) format and save it in your directory as marco-island_spot_1998-10-21_with-band-3-sliced.gis.  When you export the image, you need to go to export option and select only layer 1 (your density sliced layer), not all 4 layers.  Place the file in a folder called "Assistant" within the root of your Geography 751 folder.  Since the old IMAGINE 7.5 LAN (*.lan) format does not save color lookup tables, ERDAS created the GIS (*.gis) format specifically for this purpose. You may want to display the GIS (*.gis) image in a viewer to make sure you exported it correctly.  The export automatically creates three files - .gis, .pro, and .trl.  If you want to see your image, you need at least two files - .gis and .trl.  Please, don't forget to make a copy of .trl file, too.
 

In grading the color coded NIR band I will be looking for:
 
• Are the 3 land cover classes represented correctly (i.e. are the boundary choices within reason)?
• Were there 3 different colors assigned to the 3 different classes?
• Do the colors reasonably represent their land cover classes (e.g. red for water would be a poor choice, etc.)?