This lab was meant to introduce and explore different functions and tools within ERDAS Imagine to help enhance images to help interpret it. There are seven parts which include subset images, image fusion, radiometric enhancing, resampling, link image viewer to google earth, binary change, and image mosaking.
Objective/Goals
The goal is to create a base of understanding about how there are many different ways to enhance images to create a better image to interpret with proper techniques.
Methods
Subseting Images
Using the inquire box tool it becomes possible to create an image from the AOI. First off is to right click the image brought into ERDAS Imagine to click on inquire box. Next is to determine the location of the AOI and the size. Next,to find the next tool, it will be located in the Raster tab. Then click on subset & chip and finally create subset image. After that a window will pop up. To have the inquire box be the coordinates for the subset image click on the "From the Inquire Box." This will take the coordinates from the AOI created and bring it this window. Next is to choose a place to save it and it will be processed after hitting ok.
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| Figure 1: Subsetting using a shapefile. The image on the left shows the shapfile used, and on the right it shows the created subset image. |
First open up the more coarse image into ERDAS. Next is to open up a second viewer and open the more fine image. Then click on raster to activate the raster tools. Next, click on Pan Sharpen to find the Resolution Merge Tool. In the window that pops up input the high resolution file in the first drop down, the low resolution in the next drop down, and create an output file name in the correct folder. Also in this window under the methods area click on Multiplicative which selects the correct algorithm to use for this example. Then under Resampling techniques choose nearest neighbor. Now hit ok to run the tool.
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| Figure 2: This is an image fusion of the Eau Claire Area. The left is a lower resolution and the right has been pan sharpened to create a better quality image from the multispecral image. |
This is used to reduce Haze shown on the image. To manipulate the haze from the image the radiometric tab and then Haze reduction tool is the easiest way to get rid of it. The process was nearly the same to create an output file and run the tool.
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| Figure 3: This is an image the shows how to reduce haze on the reflective band image on the left. The right is what was created from using the haze tool. |
First, go to the Google Earth Tab. Then click the connect to Google Earth button and then once that opens up click the match GE to view button. This will match the view of the image to Google Earth. Then to make things easier click the Link GE to View and Sync GE to View. As long as GE is updated this could be useful to interpret the image.
Resampling
From the raster toolset once again select the spatial and resample pixel size Use the working image and look up the metadata to choose the correct pixel size. If needing to change, change it in the Xcell and YCell Values. For this lab it went from 30x30 to 15x15, and the square cells box needed to be checked for this lab. For this lab a nearest neighbor and bilinear interpolation method was run.
Image Mosaicking
Image mosaicking is taking two images to combine together seamlessly. This may be done because the AOI may be larger than the area of the satellite image, therefore having to put more than one together. There are two major tools used to make this possible which include Mosaic Express and Mosaic Pro. The first step is to add the images to the viewer, but there are a few steps that are needed before the addition of the second image. First highlight one of the images tab to make sure multiple images in virtual mosaic is selected. Then, back to raster tab once again check the background transparency and fit to frame are checked. Then add the image to the viewer. The mosaic express is under the raster tool set. select the image to be put together and hit run.
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| Figure 4: This is showing what happenes between just adding two images on the left and then using the mosaic express tool on the right to create a "seamless" transition. |
Mosaic Pro: The next way to do this is to choose the mosaic pro tool from the mosaic tool list found within the raster tool tab. First add the images, but before adding them click the image area options and select the compute active area button. Then set the settings and finish adding the images. Next is to match the colors which is different than the mosaic express. To do this it is imperative to choose the Color Corrections tool of the Mosaic Pro Window. This is done by using the histogram matching. The method to do that should be set to Overlap Areas. The final step is to set the output options dialog to Overlap Function to Overlay. and finally run and process the image.
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| Figure 5: This is the result of running Mosaic Pro. It produces two images that are closer in color and more blend-able at the seam. |
Binary Change (Image Differentiation)
To figure out the difference between Eau Claire 1991 and Eau Claire 2011, we compare the change in brightness of the pixels. First off, under the raster tool tab the two image functions will be found in there. The two image functions will show the 2001 and 1991 image. Then, to obtain the difference in pixels use the subtraction operation. Then under the layer scroll bar only band 4 instead of all. then run the image differentiating and open the metadata to view the histogram created.
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| Figure 6: Historgram image differentiating from Eau Claire 1991 to Eau Claire 2011 |
I2011 – I1991 + C
which means (+127 makes all the values positive):
$n1_ec_envs_2011_b4 - $n2_ec_envs_1991_b4 + 127
This creates an image that looks like this after using the equation: EITHER 1 IF ( $n1_ec_91> change/no change threshold value) OR 0 OTHERWISE.
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| Figure 7: Pixel Brightness difference output from 1991 to 2011 in Eau Claire, Wi |
Result
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| Figure 9: Result shows the changed areas based on the difference of pixel brightness. |
This lab was very thorough going through the different tools used to enhance images for better interpretation. There are many methods that may be better than others, but they are all useful in their own way, and it depends on what is trying to be achieved. These tool are important to understand and create a base of what is actually going on to study and interpret images
Sources
Satellite images
Earth Resources Observation and Science Center, United States Geological Survey.
Shapefile of the counties
Mastering ArcGIS 6th edition Dataset by Maribeth Price, McGraw Hill. 2014.
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