Lab 6

Goal and Background:

This lab is suppose to expose us to a very important image preprocessing exercise known as geometric correction. The lab is structured to develop our skills on the two major types of geometric correction that are normally performed on satellite images as part of the preprocessing activates prior to the extraction of biophysical and sociocultural information from satellite images.

Methods:

To properly correct the geometry of our images we worked within Erdas Imagine. We set the geometric model (which is a multispectral tool) which required us to bring in our two separate images. From there we accepted the defaults under the Polynomial Model Properties window and started adding our Ground Control Points (GCPs). We entered four for the first pair of images and 12 for the second pair. We needed a minimum of three for the first pair and 10 for the second pair which is determined by what order polynomial they were. Once the points were added we had to go back through and edit the points so that our Root Means Square Error Total was below a predetermined value. That is how we can measure the accuracy of our GCPs in relation to the input image. This was all that needed to be done besides exporting the resampled images as an .IMG so that we could view the geometrically corrected image.

Results:

Our first image that we corrected using 4 GCPs and the 1st order polynomial.

Our second image that we corrected using 12 GCPs and the 3rd order polynomial.

 

 

Conclusion:

Geometric Correction is an essential image preprocessing tool that we need if we are to do further analysis with our images. Without it we would not be able to calculate the brightness values from the different bands that we received from the satellite. By using spatial interpolation we can be very certain that our images are corrected and are ready for a multitude of analysis’s that can now be run.