Advertisement

Error Correction and Registration of Image Data

  • John A. Richards

Abstract

When image data is recorded by sensors on satellites and aircraft it can contain errors in geometry and in the measured brightness values of the pixels. The latter are referred to as radiometric errors and can result from the instrumentation used to record the data and from the effect of the atmosphere. Image geometry errors can arise in many ways. The relative motions of a satellite, its scanners and the earth, for example, can lead to errors of a skewing nature in an image product. Non-idealities in the sensors themselves, the curvature of the earth and uncontrolled variations in the position and attitude of the remote sensing platform can all lead to geometric errors of varying degrees of severity.

Keywords

Control Point Geometric Distortion Pixel Brightness Image Geometry Digital Count 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References for Chapter 2

  1. P. E. Anuta, 1973: Geometric Correction of ERTS-1 Digital MSS Data. Information Note 103073, Laboratory for Applications of Remote Sensing, Purdue University, West Lafayette, Indiana.Google Scholar
  2. R. Bernstein, 1983: Image Geometry and Rectification. In R. N. Colwell (Ed.) Manual of Remote Sensing, 2e, Chapter 21, Falls Church, Va. American Society of Photogrammetry.Google Scholar
  3. F. C. Billingsley, 1983: Data Processing and Reprocessing in R. N. Colwell (Ed.) Manual of Remote Sensing, 2e, Chapter 17, Falls Church, Va. American Society of Photogrammetry.Google Scholar
  4. J. D. Foley & A. Van Dam, 1982: Fundamentais of Interactive Computer Graphics, Philippines, Addison-Wesley.Google Scholar
  5. B. C. Forster, 1984: Derivation of Atmospheric Correction Procedures for Landsat MSS with Particular Reference to Urban Data. Int. J. Remote Sensing, 5, 799–817.CrossRefGoogle Scholar
  6. T. G. Moik, 1980: Digital Processing of Remotely Sensed Images, Washington, NASA.Google Scholar
  7. F. Orti, 1981: Optimal Distribution of Control Points to Minimizē Landsat Image Registration Errors. Photogrammetric Engineering and Remote Sensing, 47, 101–110.Google Scholar
  8. S. Shlien, 1979: Geometric Correction, Registration and Resampling of Landsat Imagery. Canadian J. Remote Sensing, 5, 74–89.Google Scholar
  9. L. F. Silva, 1978: Radiation and Instrumentation in Remote Sensing. In P. H. Swain & S. M. Davis (Eds.) Remote Sensing: The Quantitative Approach, N. Y., Mc-Graw-Hill.Google Scholar
  10. K. Simon, 1975: Digital Reconstruction and Resampling for Geometric Manipulation. Proc. Symp. on Machine Processing of Remotely Sensed Data, Purdue University, June 3–5.Google Scholar
  11. P. N. Slater, 1980: Remote Sensing: Optics and Optical System, Reading, Mass., Addison-Wesley.Google Scholar
  12. R. E. Turner & M. M. Spencer, 1972: Atmospheric Model for Correction of Spacecraft Data. Proc. 8th Int. Symp. on Remote Sensing of the Environment, Ann Arbor, Michigan 895–934.Google Scholar
  13. M. P. Weinreb, R. Xie, I. H. Lienesch and D. S. Crosby, 1989: Destriping GOES Images by Matching Empirical Distribution Functions. Remote Sensing of Environment, 29, 185–195.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • John A. Richards
    • 1
  1. 1.Department of Electrical Engineering, University CollegeThe University of New South Wales, Australian Defence Force AcademyCampbellAustralia

Personalised recommendations