Carasso, A.
(2008),
Calibrating Image Roughness by Estimating Lipschitz Exponents, with Applications to Image Restoration, Optical Engineering, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=51213
(Accessed October 27, 2025)
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
Secure .gov websites use HTTPS
A lock (
) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.
Calibrating Image Roughness by Estimating Lipschitz Exponents, with Applications to Image Restoration
Published
Author(s)
Abstract
Most commonly occurring images f(x,y) are not smoothly differentiable functions of the variables x and y. Rather, these images display edges, localized sharp features, and other significant fine scale details or texture. Correct characterization and calibration of the lack of smoothness in such images is important in various image processing tasks. So-called Lipschitz spaces appear to be the appropriate mathematical framework for accommodating non smooth images. The L1 Lipschitz exponent ?? for the given image, where ~0Citation
Optical Engineering
Volume
47
Issue
3
Pub Type
Journals
Download Paper
Keywords
Andromeda galaxy, APEX method, Gauss singular integral, image metrology, image roughness, Lipschitz exponents
Citation
Issues
If you have any questions about this publication or are having problems accessing it, please contact [email protected].
Created March 3, 2008, Updated January 27, 2020