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Image Processing I
Contents

In this new series of chapters to follow, I will try to give a very coarse introduction to Image Processing as done with IDRISI. Often users aren't aware of the fact, that IDRISI provides a complete 'starter-kit' to perform classical image processing. The next pages shall roughly guide you through some techniques and methods in that fields.

What you will not find here, is the theory behind (as much as necessary only :), so help yourself with one of the excellent textbooks about image interpretation and remote sensing. Also refer to the online Remote Sensing Tutorial at Goddard Space Flight Center, NASA (European users try our local mirror).

The term image processing is used here mainly in the context of satellite classification and related aspects.

We will touch several items, starting with an example, how to (1) import satellite data. After that, a closer look on (2) enhancement functions (such as STRETCHing, FILTERing, using HISTOgrams) follows. Closely related (3) visualizational aspects (e.g., band combinations, COMPOSIT images and removing redundancies) will be covered then. (4) Classification methods presented here will comprise unsupervised (CLUSTER) and supervised techniques (defining training areas, creating, comparing and editing spectral signatures: MAKESIG, EDITSIG, SIGCOMP, PIPED, MINDIST, MAXLIKE). (5) Accuracy checking should conclude the whole (ERRMAT).

among several fine books:

1. Thomas M. LILLESAND & Ralph W. KIEFER, 1994^{3rd ed.}: Remote Sensing and Image Interpretation. John Wiley & Sons, New York
   Eric C. BARRETT & Leonard F. CURTIS, 1992^{3rd ed.}: Introduction to Environmental Remote Sensing. Chapman & Hall, London

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