Chapter 3. Statistical Description of Images
Published Online: 17 OCT 2001
DOI: 10.1002/0470841907.ch3
Copyright © 1999 John Wiley & Sons, Ltd
Book Title

Image Processing: The Fundamentals
Additional Information
How to Cite
Petrou, M. and Bosdogianni, P. (2001) Statistical Description of Images, in Image Processing: The Fundamentals, John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/0470841907.ch3
Publication History
- Published Online: 17 OCT 2001
ISBN Information
Print ISBN: 9780471998839
Online ISBN: 9780470841907
- Summary
- Chapter
Keywords:
- ergodicity;
- random field;
- correlation matrix;
- Karhunen–Loeve transform;
- least mean square error approximation
Summary
This chapter gives the basic theory behind the description of an image as a random field. All fundamental concepts necessary to define a random field are explained, starting from the concept of a random variable. It includes a detailed analysis on the assumption of ergodicity, what it means and when it is valid. It defines Karhunen–Loeve transform and gives worked out examples with step by step calculation of the correlation or covariance matrix of an image, its Karhunen–Loeve transform and the basis images in terms of which Karhunen–Loeve transform expands it. Everything is demonstrated with a help of small 3 by 3 or 4 by 4 images where all steps of the analysis are shown. Results of truncating the Karhunen–Loeve transform are compared with those of chapter 2 using the same 8 by 8 grey image.
