Geometric Correction

Goal
Background: The goal of this lab was to gain experience in the preprocessing exercise of geometric correction.

Methods
Image-to-Map:
Method: For this method, an aerial image and a map image of Chicago were used. In order properly begin rectifying, the second viewer must contain the image to be rectified. After this, the Multispectral tab was opened and the Control Points button was picked from the toolbar. Polynomial was selected from the newly opened Set Geometric Model window. As the next windows came up, the default settings were accepted for this model. The second image was then brought in for rectification and the defaults were accepted to bring this image in. As this is a first order polynomial, it will only take a few points to gain ample rectification of the imagery. In order to start entering geometric control points (GCPs), the default GCPs were deleted, the images were fitted to screen and the Create GCP tool was selected. After placing the first point, the button was clicked again and a control point was placed on the second image in roughly the same spot. This was done four times, with a change occuring after the third GCP placement. After the third, the bar on the bottom of the window read "Model solution is current". When the next point was plotted, it was plotted for both of the maps at once. After the GCPs were placed, accuracy was worked on. The Root Mean Square (RMS) error shows how accurate the image is. For this image, the analyst was able to get the RMS error to 0.4850. The recommended RMS value for first order polynomials is 2.0. The result can be seen in Figure 1.

Figure 1: Image-to-map rectification. This image shows the rectified image, on the right, and the image that was used to rectify it on the left.

Once the RMS value has been lowered, the geometric correction was carried out by selecting Multipoint Geometric Correction and then Display Resample Image Dialog.

Image-to-Image:
Method: This method was carried out much in the same way as the Image-to-map rectification. An image of the Sierra Leone was brought in for this model. A difference with this method was, instead of using a first order polynomial, a third order polynomial was used. This was chosen for greater accuracy, and it requires at least nine points to be taken instead of just three. All of the points were scattered throughout the map to ensure that there was no distortion and the RMS value was lowered below 0.5. In this case, the analyst was able to lower the RMS error to 0.2805. This can be seen in Figure 2.

Figure 2: Image-to-image rectification. This image shows the rectified image, on the right, and the image that was used to rectify it on the left.

Results
This lab was a great start to understanding geometric corrections. A few steps were repeated in order to gain a better understanding but in the end, an understanding was achieved and the initial processes of geometric corrections were understood.