Differentiation and regularization

Part of the Computational Imaging and Vision book series (CIVI, volume 27)

Regularization is the technique to make data behave well when an operator is applied to them. Such data could e.g. be functions, that are impossible or difficult to differentiate, or discrete data where a derivative seems to be not defined at all. In scale-space theory, we realize that we do physics. This implies that when we consider a system, a small variation of the input data should lead to small change in the output data.

Keywords

Assure Convolution Arsenin 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer Science + Business Media B.V. 2003

Personalised recommendations