Abstract
Preprocessing algorithms frequently form the first processing step after capturing the image, as you will see in many of the examples in the following chapters. Therefore, we will start the overview chapters with an introduction to image preprocessing. Gonzalez and Woods (2008) present a comprehensive overview. To give a clear conceptual idea of the effect of the various operations we will use very simple synthetic sample images in this chapter. The application examples in the following chapters use many of these algorithms on real-world industrial images.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
To avoid even more complicated abbreviations, we will always assume to work with images of 256 gray levels.
- 2.
In general, we would have to write this as g/(g max  + 1).
- 3.
We differ here from other literature that uses a scaling factor of 1/8. We will demonstrate that 1/4 is sufficient to assure a limitation to the gray value range.
- 4.
Please note that this is not a matrix multiplication where the scalar products of rows and columns are computed. Multiplication is done pixel by pixel.
References
Bronstein IN, Semendjajew KA, Musiol G, Mühlig H (2005) Taschenbuch der Mathematik. 6th edn. Harri Deutsch, Frankfurt a. M
Gonzalez RC, Woods RE (2008) Digital image processing, 3rd edn. Pearson Education, Upper Saddle River
Jähne B (2005) Digitale Bildverarbeitung, 6th edn. Springer, Berlin
Nischwitz A, Fischer M, Haberäcker P (2007) Computergrafik und Bildverarbeitung, 2nd edn. Vieweg, Wiesbaden
Rosenfeld A, Kak AC (1982) Digital picture processing, 2nd edn. Academic Press, New York
Russ JC (2007) The image processing handbook, 5th edn. CRC Press, Boca Raton
Sonka M, Hlavac V, Roger B (2008) Image processing, analysis, and machine vision, 3rd edn. Cengage Learning, Stamford
Steger C, Ulrich M, Wiedemann C (2008) Machine vision algorithms and applications. Wiley-VCH-Verlag, Weinheim
Tönnies KD (2005) Grundlagen der Bildverarbeitung. Pearson Studium, München
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Demant, C., Garnica, C., Streicher-Abel, B. (2013). Overview: Image Preprocessing. In: Industrial Image Processing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33905-9_2
Download citation
DOI: https://doi.org/10.1007/978-3-642-33905-9_2
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33904-2
Online ISBN: 978-3-642-33905-9
eBook Packages: Computer ScienceComputer Science (R0)