Remote Sensing Lab 6

Goal and Background

The goal of this lab is to introduce the preprocessing method of geometric correction. Throughout the laboratory exercise, the two types of geometric correction will be discussed and each method will be practiced.

1.Image-to-Map Rectification:

This type of interpolation transforms the image data pixel coordinates using the map coordinate components.

2. Image-to-Image Rectification:

This method is the same process of correction however; the reference image is one which has already been corrected.

Methods
In order to gain a firm understanding of the techniques above, ERDAS Imagine 2013 was used. The processes used to achieve the goal of the lab are presented below.

Image-to-Map Rectification:

Rectification is the process where a data file coordinate is converted to another grid and coordinate system, known as a reference system. Using the map coordinate counterparts the image data pixel coordinates are transformed resulting in a planimetric image. The first step in ERDAS Imagine 2013 to begin this transformation is to select the Control Points option in the Multispectral tool list. Using this tool the two images (Fig. 1) will be used to perform the image-map-rectification method of geometric correction.

(Fig. 1) The reference image is the map on the left and the input image used is the one on the right.

Once the Multipoint Geometric Correction window has started, we will be selecting the 1st order polynomial transformation. Since we are performing a 1st order transformation, a minimum of 3 GCFs much be implemented as shown below in Fig. 2. Once the order of the polynomial transformation has been determined the process of creating the individual GFCs can begin. After the default points are deleted, use the "Create GCP" tool to add points on both the reference and input image in the same region of each map the data will be recorded in the pane below the two images (Fig. 3). It is important to make sure that the RMS error is low. This references how accurate the geometric correction of the input image is before a final output image is produced. Once the RMS error level is below 2 a final, geometrically corrected image is created (Fig. 4).

(Fig. 2) One of the first steps in performing a Multipoint Geometric Correction is determining the order of the polynomial transformation. For this particular lab we will be using a first order (as is shown in the image above).

(Fig. 3) The image displays the input image (left) and the reference image (right) once the 4 new GCFs have been manually applied and adjusted to make the RMS Error below 2.

(Fig. 4) Output image produced after the original image (Fig. 1 left) was geometrically corrected by a first order polynomial transformation.

Image-to-Image Rectification:

The process used to perform geometric correction using this method is the same as the Image-to-Map rectification except the reference image used is an already corrected image. The two original images (Fig. 5) are going to be geometrically corrected using the same steps as the Image-to-Map Rectification method. The only main difference is that the polynomial transformation that will be applied to these images is 3rd order. Since we are applying a 3rd order polynomial transformation we need a minimum of 10 GCFs in order to perform an accurate geometric correction (Fig. 6). After the total RMS error has been decreased to under 1, a final geometrically corrected output image can be produced and the rectification is complete.

(Fig. 5) The two images are layered to show the differences in the original images using the swipe tool it becomes more obvious. The image in the background is the reference image and the one in the foreground is the input image.

(Fig. 6) Once a minimum of 10 GCFs is added to the reference and input image and the total RMS error is below 1 an geometrically corrected output image can be produced. 

Results

Through this laboratory exercise, the image analyst developed skills on both the Image-To-Map and Image-to-Image rectification methods of geometric correction. This type of preprocessing is one that is commonly performed on satellite images before data or information is extracted from the satellite image.

Sources

Data used in this lab was provided by Dr. Cyril Wilson and collected from the following sources: (1) 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. Ground control points (GCPs) will be collected from the USGS 7.5 minutes DRG and used it to rectify the TM image. The same will be done for the Sierra Leone images used in this lab.