Lab 6

Goals and Background

The purpose of this lab is to introduce students to geometric correction using both Image-to-map and Image-to-image rectification.

Methods

To begin the lab imported an image of the Chicago area into Erdas Imagine. This image was distorted and needed to be corrected using image-to-map rectification. To do this I used the Control Points function under the Multispectral tools tab. This function allowed me to place Ground Control Points (GCPs) onto another image to improve its spatial accuracy. I chose to place the GCPs onto a reference map and perform a first order polynomial transformation. I then brought in the digital reference map and placed four GCPs spaced across the images, placing them at places such as road intersections. After adjusting the GCPs to make sure they had minimal error I ran the Display Resample Image tool that created my newly resampled using the nearest neighbor method.

The next section of the lab involved following a similar process to correct a spatial distorted image. Instead of using a reference map in the previous section I used an image of the same area. I brought in the image and used the Control Points function and adjusted the setting to create a third order polynomial transformation. I brought in the reference image and began to plot my GCPs. Because I was performing a third order polynomial transformation I needed to place a minimum of 9 GCPs. I plotted 12 to ensure that the new image would be more spatially accurate. Once the GCPs were adjusted, I resampled the image using Bilinear Interpolation, which made the image more spatial accurate but it did reduce the contrast in the newly created image.

Results

Image-to-map rectification

Image-to-image rectification

Resampled image using Bilinear Interpolation