5.2
Geometric Correction 
of Remotely Sensed Data
R. Douglas Ramsey

Department of Geography and Earth Resources
Utah State University
Logan, Utah, 84322-5240
Direct Comments to:Doug@nr.usu.edu
The original site for this module can be found at :
Utah State University Department of Geography


 

Introduction

Digital images collected from airborne or spaceborne sensors often contain systematic and unsystematic geometric errors. Some of these errors can be corrected by using ephemeris of the platform and known internal sensor distortion characteristics. Other errors can only be corrected by matching image coordinates of physical features recorded by the image to the geographic coordinates of the same features collected from a map or global positioning system (GPS).

Geometric errors that can be corrected using sensor characteristics and ephemeris data include scan skew, mirror-scan velocity variance, panoramic distortion, platform velocity, and perspective geometry.
Errors that can only be accounted for by the use of GCP's include the roll, pitch, and yaw of the platform and/or the altitude variance (Berstein, 1983).

Definitions

There are a number of terms that deal with geographic correction of remotely sensed data. These terms are sometimes used interchangeably and in confusion with the other.Ephemeris: Any tabular statement of the assigned places of a celestial body for regular intervals (Websters Dict.). For example, the solar ephemeris provides the exact location of the sun at any given time of the day or year.Geocoding: Geographical referencing or coding of data. (Jensen, 1986)Ground Control Point (GCP): A specific pixel on an image or location on a map whose geographic coordinates are known. GCP's are used to correct geometric distortion in an image by matching image coordinates with map coordinates. Image and map coordinates are used to compute the transformation matrix for use in rectifying the image.

 Linear Transformation: The transformation of coordinates from one system to another (image to map) using a linear algebraic (1st order polynomial) formula

 Non-Linear Transformation: The transformation of coordinates from one system to another (image to map) using a non-linear algebraic (Nth order polynomial) formula

 Rectification: The process by which the geometry of an image is made planimetric. (Jensen, 1986)
Registration: The process of geometrically aligning two or more sets of image data such that resolution cells for a single ground area can be digitally or visually superimposed. A map coordinate system may not be involved.

 Resampling: The process of extrapolating data values to a new grid. Resampling is the step in rectifying an image that calculates pixel values for the rectified grid from the original data grid.

 Root Mean Square Error (RMS):The RMS is the error term used to determine the accuracy of the transformation from one coordinate system to another. It is the difference between the desired output coordinate for a GCP and the actual
 
 

Image to Ground Geocorrection

The correction of digital images to ground coordinates using ground control points collected from maps or ground GPS recognaisance.
 

Image to Image Geocorrection

Image to Image correction involves matching the coordinate systems of two digital images with one image acting as a reference image and the other as the image to be rectified.
 
 
 

Image Resampling Methods

Nearest Neighbor - Uses the input cell value closest to the output cell as the assigned value to the output cell

Bilinear Interpolation - Calculates the output cell value by calculating the weighted average of the four closest input cells (a 2x2 array) based on distance.

Cubic Convolution - Calculates the output cell value by calculating the weighted average of the closest 16 input cells (a 4x4 array) based on distance.


 


Exercises

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References

Bernstein, R., 1983. Image Geometry and Rectification. Chapter 21 in The Manual of Remote Sensing. R. N. Colwell, ed., Bethesda, MD. American Society of Photogrammetry, 1:875-881.

Campbell, J. B. 1987. Introduction to Remote Sensing. The Guilford Press. 551pp.

Lillesand, T. M. and R. W. Kiefer. 1994. Remote Sensing and Image Interpretation, 3rd Ed. John Wiley and Sons, Inc. 750pp.

Jensen, J. R. 1996. Introductory Digital Image Processing: A Remote Sensing Perspective. Prentice Hall Inc., 316pp.