Remote Sensing - Lab 6: Geometric Correction

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Background and Objectives

Prior to the extraction of biophysical and sociocultural information from satellite images, the analyst must perform some preprocessing activities. The following lab exercise is designed to introduce the concept of image preprocessing known as Geometric Correction. There are two major types of geometric correction that are normally performed; Image-to-Map Rectification and Image-to-Image Registration.

Image-to-Map Rectification

In this part of the lab exercise, the analyst will use a United States Geological Survey (USGS) 7.5 minute digital raster graphic (DRG) image of the Chicago Metropolitan Statistical Area and adjacent regions to correct a Landsat TM image of the same area. In order to accomplish this, ground control points (GCPs) must be collected from the USGS 7.5 minute DRG and used to rectify the Landsat TM image.

Image-to-Image Registration

In the second part of the lab exercise, the analyst will use an already corrected Landsat TM image for Eastern Sierra Leone to rectify a geometrically distorted image of the same area.

Methods

This section will cover the process and steps taken to preprocess images using the two major types of geometric correction. 

Image-to-Map Rectification

  • Open both the Digital Raster Graph (DRG) and the image to be rectified in separate, side-by-side screens, as seen in Image 1.1.
Image 1.1. Reference Map (Left) and Image to be Rectified (Right)
  • Select the image to be rectified and click the Multispectral tab > Control Points. The 'Set Geometric Model' dialog box opens. Select the 'Polynomial' geometric model.
  • Choose 'Image Layer (New Viewer)' as the location to collect reference points from and load the DRG as the reference image layer, accepting the default setting on the Polynomial Model Properties dialog. 
  • The Multipoint Geometric Correction window opens, containing both images. This is where GCPs will be selected.
  • Click the Create GCP tool and begin adding pairs of GCPs to the reference image and the image to be rectified, as seen in Image 1.2. Four pairs of GCPs should be created and the RMS Error should be below 2.0.
Image 1.2. Multipoint Geometric Corection window

Image-to-Image Registration

  • The Image-to-Image Registration process follows the same steps as the Image-to-Map Rectification process, except instead of a reference map, a reference image is used. The reference image is located on the right side of Image 2.1.

Image 2.1. Reference Image (Left) and Image to be Rectified (Right)
  • On the Polynomial Model Properties dialog, change the Polynomial Order to '3'. In order to perform a 3rd Order Polynomial, a minimum of 10 GCPs is required. Use the reference table in Table 1.1 to find the minimum number of GCPs needed for each Order of Transformation.
Table 1.1. Minimum GCPs Required for Transformations
  • Place 12 matching pairs of GCPs and reposition them until the RMS Error has dropped below 1.0.
  • In the Display Resample Image dialog, select Bilinear Interpolation as the Resample Method to generate the output image.

Results

This section features the outputs of the two geometric correction methods that were used in this lab exercise.

Image-to-Map Rectification

After placing and repositioning the four pairs of GCPs to reduce the RMS Error, the image is ready to be rectified based on the USGS reference map. This method of geometric correction uses Spatial Interpolation to establish a coordinate transformation of the input image. In the case of this exercise, a First Order Polynomial model was used. Adding more GCPs would increase the accuracy of the transformation, but this is only necessary when working with highly variable terrain, such as mountainous areas. The output of the Image-to-Map Rectification from this exercise can be seen in Image 3.1, with a total RMS Error of 1.7539. The RMS Error should always be below 2.0 to ensure transformation accuracy, but an ideal RMS Error would be below 0.5.

Image 3.1. Image-to-Map Rectification GCP pairs

Image-to-Image Registration

In the Image-to-Image Registration of the satellite images over Eastern Sierra Leone, 12 GCPs pairs were created for a 3rd Order Polynomial. A 3rd Order Polynomial with a Bilinear Interpolation resample method was used to ensure higher accuracy for the coordinate transformation. The output can be seen in Image 3.2. The swipe feature has been activated in the image to show that transformed image matches with the reference image. Notice the river within the red box and how it transitions smoothly from the transformed output image and the reference image. The RMS Error of this transformation was 0.3900.

Image 3.2. Image-to-Image Registration Output

Sources

Landsat TM Satellite Images courtesy of Earth Resources Observation and Science Center, U.S. Geological Survey 

Digital Raster Graphic (DRG) courtesy of Illlinois Geospatial Data Clearing House

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